Research ArticleA Comparison of Central Composite Design and TaguchiMethod for Optimizing Fenton Process

Anam Asghar Abdul Aziz Abdul Raman and Wan Mohd Ashri Wan Daud

Chemical Engineering Department Faculty of Engineering University of Malaya 50603 Kuala Lumpur Malaysia

Correspondence should be addressed to Abdul Aziz Abdul Raman azizramanumedumy

Received 21 April 2014 Revised 22 July 2014 Accepted 6 August 2014 Published 27 August 2014

Academic Editor Seval Kutlu Akal Solmaz

Copyright copy 2014 Anam Asghar et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In the present study a comparison of central composite design (CCD) and Taguchi method was established for Fenton oxidation[Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were identified control variables while COD and decolorization efficiency were selected

responses 1198719orthogonal array and face-centered CCD were used for the experimental design Maximum 99 decolorization and

80 COD removal efficiency were obtained under optimum conditions 119877 squared values of 097 and 095 for CCD and Taguchimethod respectively indicate that both models are statistically significant and are in well agreement with each other FurthermoreProb gt 119865 less than 00500 and ANOVA results indicate the good fitting of selected model with experimental results Neverthelesspossibility of ranking of input variables in terms of percent contribution to the response value has made Taguchi method a suitableapproach for scrutinizing the operating parameters For present case pHwith percent contribution of 8762 and 662was rankedas the most contributing and significant factor This finding of Taguchi method was also verified by 3D contour plots of CCDTherefore from this comparative study it is concluded that Taguchi method with 9 experimental runs and simple interaction plotsis a suitable alternative to CCD for several chemical engineering applications

1 Introduction

Fenton oxidation is an efficient and widely applied AOPswhich utilizes ferrous iron (Fe+2) and hydrogen peroxide(H2O2) under acidic conditions to produce hydroxyl radi-

cal (HO∙) (reaction 1) Formation of HO∙ is advantageousbecause it is highly oxidative (119864 = 28 eV) and nonselectivein nature [1 2] However the performance of Fenton reactionis influenced by several parameters such as pH reaction timeinitial concentrations of Dye H

2O2 and Fe+2 catalysts [3 4]

Moreover excess consumption of chemicals (Fe+2 salt H2O2

acidbase) and high cost of H2O2have made this process

economically nonviable [5 6] Therefore a systematic way ofplanning execution and statistical evaluation of process isrequired which is only possible through optimization process[7] Consider

Fe+2 +H2O2997888rarr Fe+3 +HO∙ +OHminus (1)

In context to any engineering problem optimization refers toimproving the performance of system or process by applying

several variables in different combinations to get the bestpossible result [8] Optimization techniques are broadlyclassified into two categories univariate and multivariateapproach Univariate approach also known as one-factor-at-time (OFAT) approach involves variation of one parameterat a time Nevertheless multivariate approach has severaladvantages over OFAT For example [9] (1) it provides globalknowledge in its whole experimental domain while OFATgives local knowledge where experiment is performed (2) itis possible to study the interaction between the factors andnonlinear relationships with the responses (3) the number ofexperiments required to optimize the process is considerablylesser than that of OFAT approach (4) within the experi-mental domain at each point quality of the information ishigher and can be known through the leverage The stepwiseexecution of optimization is presented in Figure 1

Driven by the need of reducing the number of experi-ments cost time and physical efforts design of experiment(DOE) is an important statistical and mathematical toolfor solving complex and multifactor engineering problems

Hindawi Publishing Corporatione Scientific World JournalVolume 2014 Article ID 869120 14 pageshttpdxdoiorg1011552014869120

2 The Scientific World Journal

Conducting confirmation experiments

Yes

Optimization

Evaluate the parameters and type

of design chosen

NoObjective achieved

experiments

Model fitnessvariation

ANOVA

Analysis and evaluation of models

Selecting process factors

Screening factors

Significant factors

Yes

No

Eliminateadd factors

Defining problems and responsesvariables

Selecting design (factorial RSM Taguchi etc) and planning

Actual and predicted

Figure 1 Flow chart for optimization

It includes response surface methodology (RSM) factorialdesign and in some special cases artificial neural network(ANN) [10] However central composite design (CCD) D-optimal and Box-Behnken are found to be widely used opti-mization techniques for Fenton oxidation [11ndash13] because ofthe advantage of optimizing multifactor problems with opti-mum number of experimental runs Besides these methodshave limitation of increased number of experiments if severalfactors were selected for process optimization For exampleBox-Behnken suggests 54 experiments if six factors arerequired to be studied and with CCD this number increasesup to 80Thus with multiple factors these techniques are notappropriate because it increases the cost of chemicals timeand physical efforts Therefore a simplified design strategy isrequired that can be used to overcome these problems

Taguchi method is a robust statistical tool that allowsthe independent evaluation of the responses with minimumnumber of experiments It employs orthogonal arrays forexperimental design and 119878119873 ratio instead of responsesitself to determine the optimum settings of control fac-tors and thus neglects the variations caused by uncontrol-lable factors [14] With this method experimental results

can be analyzed through 119878119873 ratio and ANOVA withsimultaneously evaluating the significance of the factors interms of their contribution to the response values

Available works on optimization of Fenton oxidationmainly focus on CCD under RSM [15ndash17] Neverthelessfewer studies based on Taguchi method are found in theliterature [18ndash20] but which technique is better for Fentonoxidation is still not inclusive Therefore this study wasplanned to compare two experimental design techniques andFenton oxidationwith four parameters such as [pollutants]iniDye Fe+2 H

2O2 Fe+2 and pH was selected as a case study

For comparison frequently used CCD and robust Taguchiexperimental design technique were chosen with a specialfocus on comparing the optimization and detailed statisticalanalysis of the experimental results

2 Background

21 Response Surface Methodology and Central CompositeDesign RSM a multivariate statistical tool consists of agroup of mathematical and statistical techniques that arebased on the fit of empirical models to the experimental

The Scientific World Journal 3

Analysis

Decision

Initial phase

Obtaining model equation

Comparing predicted and actual values

Model graphs (2D and 3D contour)

(significant)Lack of fitness (significant)

Optimization

Confirmation experiment

Selecting process factors and their levels

desirable

Conducting experiments

Selecting responses

ANOVA

Model selection

Or

Yes

Objective achieved

Evaluate the reason

No

Determining value of 120572 face centered value is

Adjusted andpredicted R

2 valueAdequate precision

(SN gt 4) F test

Figure 2 Central composite design flow diagram

data obtained in relation to experimental design [21] Itemploys lower order polynomial [22] and it has already beenproved to be a reliable statistical method for chemical processapplications [23 24]

In RSM category CCD which is appropriate for fittingsecond order polynomial equations has been frequentlydiscussed for optimizing several research problems A CCDhas three groups of design points [25]

(a) two-level factorial or fractional factorial design points(2119896) consisting of possible combinations of +1 and minus1levels of factor

(b) 2119896 axial points (sometimes called star points) fixedaxially at a distance say 120572 from the center to generatequadratic terms

(c) center points which represent replicate terms centerpoints provide a good and independent estimate ofthe experimental error

Considering these points the number of experimentsdesigned by CCD will be

119873 = 1198962 + 2119896 + 119899 (2)

where 119873 is the total number of experiments 119896 is thenumber of factors studied and 119899 is the number of replicatesCentral composite design under RSM is normally performedeither by using design expert software or Minitab In thisstudy design expert (Version 8071) is used as optimizationsoftware The steps that will be followed for the centralcomposite design (CCD) are presented in Figure 2

4 The Scientific World Journal

In CCD value of alpha is important to calculate as itcould determine the location of axial points in experimentaldomain Depending on alpha value design is sphericalorthogonal rotatable or face centered Practically it is inbetween face centered and spherical and is calculated as

120572 = (2119896)025

(3)

Value of alpha equals 1 is desirable because it ensures theposition of axial point within factorial portion region It iscalled face centered design and offers three levels for thefactors to be put in the experimental design matrix

Experimental results obtained are analyzed usingresponse surface regression procedure of statistical analysissystem Corelation between responses and independentvariables is obtained by fitting them into second orderpolynomial equation [10]

119884 = 1205730+119896

sum119894=1

120573119894119909119894+119896

sum119894=1

1205731198941198941199092119894119894+119896

sum119894=1

119896

sum119894 =119895=1

120573119894119895119909119894119909119895+ 120576 (4)

Here 119884 represents the responses 119896 is the total numberindependent factors 120573

0is an intercept 119894 119894119894 and 119894119895 with

120573 represent the coefficient values for linear quadratic andinteraction effects respectively and 119909

119894and 119909

119895in the above

equation show the coded levels for independent variables[26]

22 Taguchi Method and Signal to Noise Ratio Taguchimethod is a robust and multiparameter optimization statisti-cal technique which employs fewer numbers of experimentsto identify and optimize parameters to achieve desiredresponse [27 28] It is a simple and systematic way ofdetermining the effect of factors on responses and optimumcondition of the factors Taguchi method utilizes full frac-tional design called orthogonal arrays and ANOVA as a toolfor analysis [29] Orthogonal arrays are the minimum setof experiments which represents the various combinationsof factors Output of the orthogonal arrays is optimizedwith respect to signal to noise ratio (119878119873) of the responsesinstead of the responses itself and thus it reduces the processvariability [30] This feature marks the difference betweenthe conventional statistical technique and Taguchi methodThe stepwise procedure for Taguchi method is represented inFigure 3

In Taguchi method 119878119873 ratio is the measure of thedeviation of the response from the desired value Hereldquosignalrdquo implies the mean value while ldquonoiserdquo shows thestandard deviation term It means that lower variability inthe process is ensured through maximizing the 119878119873 ratioHowever depending on the type of response desired Taguchiclassified 119878119873 ratio into three categories smaller-the-betterlarger-the-better and nominal-the-better [31]

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (5)

Identifying factors and responses

Selecting suitable orthogonal array

Conducting experiments

ANOVA analysis

Determining optimum value

Confirming experiments

Transforming responses into SN ratios

Figure 3 Taguchi orthogonal array

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (6)

Larger is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1

1199102119894

) (7)

Nominal is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1205832

1205902) (8)

where 120583 = (1119899)sum119899119896=1119910119894 1205902 = (1(119899 minus 1))sum119899

119896=1(119910119894minus 120583)2

And 119910119894represents response variables and ldquo119899rdquo donates the

number of experimentsOne of the distinct features of Taguchi method is that

it determines optimum value in the form of 119878119873 ratio Thepredicted 119878119873 ratio at optimal process conditions can becomputed by the following mathematical equation [32]

119878119873predicted = 119878119873 +sum(119878119873119895minus 119878119873) (9)

where 119878119873 shows the mean of all 119878119873 ratios 119878119873119895is the

119878119873 ratio at the optimal level for each parameters and 119899 isthe number of process parameters that significantly affect theprocess

3 Case Study

In this study Fenton oxidation of synthetic dye acid blue113 has been taken as a case study for comparing twooptimization techniques that is CCD and Taguchi method

The Scientific World Journal 5

31 Experimental Details For performing Fenton oxidationall reagents used were of analytical grade and procured fromMerck Sdn Bhd Malaysia Synthetic dye acid blue 113 waspurchased from Sigma-Aldrich (M) Sdn Bhd Malaysia

For performing Fenton oxidation stock solutions of333 gL of H

2O2and 100 gL of FeSO

4sdot7H2O were prepared

All solutions were prepared by using distilled water Fentonoxidation experiments were performed in batch laboratoryscale Erlenmeyer flask (500mL capacity) equipped with amagnetic stirrer For each test 150mL of acid blue 113 dyesolution was placed into flask and pH was adjusted byusing 05M H

2SO4or 1M NaOH solution according to the

designed experiment Desired amounts of FeSO4sdot7H2O and

H2O2solutions were added to the dye solution respectively

while stirring at 150 rpm The start time was recorded whenH2O2solution was added After 90 minutes pH of the

solution was measured and sufficient amount of 1M NaOHsolution was added to increase pH above 11 to stop the reac-tion This is because in alkaline conditions Fe+2 precipitatesout as Fe+3 and H

2O2decomposes into oxygen Then after

2 hrs of settling time the supernatant was filtered through045 120583m Millipore filter and subjected to various analysesAll experiments were performed at room temperature andatmospheric pressure

32 Analysis pH measurements of the solution were carriedout with the aid of pH meter (CyberScan pH 300 Eutec-tic instruments) Quantitative measurement of the residualH2O2in treated wastewater was carried out by using per-

oxide test strips (Merck) The raw and treated samples werescanned using UV-spectrophotometer (Spectroquant Pharo300 Merck) And decolorization efficiency of the treatedsample was calculated as follows

Decolorization () = (1 minusAbs119891

Abs∘

) times 100 (10)

COD measurements were made according to the standardmethod (APHA AWWA and WFE 1998) For this CODtest cell supplied by Merck was heated in thermoreactor(Spectroquant TR 420) after adding required amount of thesample followed by the subsequent measurement in UV-spectrophotometer according to the standard method AndCOD removal efficiency is calculated as

COD () = (1 minusCOD119891

COD∘

) times 100 (11)

4 Result and Discussion

41 Central Composite Design All experiments for Fentonoxidation were designed according to RSM using centralcomposite design (CCD) with the aid of design expert(Version 8071) According to the literature review the mostimportant parameters which affect the efficiency of Fentonprocess are pH initial concentrations ofDye Fe+2 andH

2O2

[4 33 34] Therefore [Dye]ini pH H2O2 Fe+2 (wtwt) and

Dye Fe+2 (wtwt) ratios were chosen as control variables tobe optimized using CCD as given in Table 1

Table 1 Experimental range and levels of process variables

Independent numericalvariables Coded Low actual

valueHigh actual

valueDye (mgL) 119883

1100 300

H2O2 Fe+2 (wtwt) 119883

25 25

Dye Fe+2 (wtwt) 1198833

10 50pH 119883

42 9

Total 30 runs with 16 factorial 8 Axial and 6 centerpoints were suggested by design expert to optimize theresponses that is COD and decolorization efficiency Basedon the proposedmodel the following quadratic equation wasdeveloped to predict the dependent variables (responses) interms of independent variables and their interactions

119884 = 1198870+ 11988711199091+ 11988721199092+ 11988731199093+ 11988741199094+ 119887111199091

2 + 119887221199092

2

+ 119887331199093

2 + 11988741199094

2 + 1198871211990911199092+ 1198871311990911199093+ 1198871411990911199094

+ 1198872311990921199093+ 1198872411990921199094+ 1198873411990931199094

(12)

where 119884 is the response variable (COD removal or decol-orization efficiency) 119887

0is constant 119887

1 1198872 1198873 and 119887

4are

coefficient for linear effects 11988711 11988722 11988733 and 119887

44are quadratic

coefficient and 11988712 11988713 11988714 11988723 11988724 and 119887

34are interaction

coefficients [36] respectively

42 Model Results for Fenton Oxidation of Acid Blue 113

421 Model Fitting and Analysis of Variance (ANOVA)Different concentrations of CI acid blue dye 113 were pre-pared and Fenton oxidation was performed under differentconditions according to the experimental runs as suggestedby CCDmodel Based on experimental results the followingempirical second order polynomial equationswere developedshowing the interactions between the proposed independentvariables to obtain decolorization and COD removal efficien-cies

COD = 6418620 minus 020098 lowast (Dye) + 070063

lowast (H2O2 Fe+2) + 175866 lowast (Dye Fe+2)

lowast 042339 lowast (pH) + 348465119864 minus 003

lowast (Dye lowast Dye Fe+2) minus 174043119864003

lowast (Dye lowast Dye Fe+2) + 0013948 lowast (Dye lowast pH)

+ 0031013 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 013479 lowast (Dye Fe+2) lowast (pH)

+ 388643119864 minus 004 lowast (Dye2) minus 0066812

lowast (H2O2 (Fe+2)

2

) minus 0021456 lowast (Dye (Fe+2)2

)

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Active and Passive Electronic Components

Control Scienceand Engineering

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Submit your manuscripts athttpwwwhindawicom

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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DistributedSensor Networks

International Journal of

2 The Scientific World Journal

Conducting confirmation experiments

Yes

Optimization

Evaluate the parameters and type

of design chosen

NoObjective achieved

experiments

Model fitnessvariation

ANOVA

Analysis and evaluation of models

Selecting process factors

Screening factors

Significant factors

Yes

No

Eliminateadd factors

Defining problems and responsesvariables

Selecting design (factorial RSM Taguchi etc) and planning

Actual and predicted

Figure 1 Flow chart for optimization

It includes response surface methodology (RSM) factorialdesign and in some special cases artificial neural network(ANN) [10] However central composite design (CCD) D-optimal and Box-Behnken are found to be widely used opti-mization techniques for Fenton oxidation [11ndash13] because ofthe advantage of optimizing multifactor problems with opti-mum number of experimental runs Besides these methodshave limitation of increased number of experiments if severalfactors were selected for process optimization For exampleBox-Behnken suggests 54 experiments if six factors arerequired to be studied and with CCD this number increasesup to 80Thus with multiple factors these techniques are notappropriate because it increases the cost of chemicals timeand physical efforts Therefore a simplified design strategy isrequired that can be used to overcome these problems

Taguchi method is a robust statistical tool that allowsthe independent evaluation of the responses with minimumnumber of experiments It employs orthogonal arrays forexperimental design and 119878119873 ratio instead of responsesitself to determine the optimum settings of control fac-tors and thus neglects the variations caused by uncontrol-lable factors [14] With this method experimental results

can be analyzed through 119878119873 ratio and ANOVA withsimultaneously evaluating the significance of the factors interms of their contribution to the response values

Available works on optimization of Fenton oxidationmainly focus on CCD under RSM [15ndash17] Neverthelessfewer studies based on Taguchi method are found in theliterature [18ndash20] but which technique is better for Fentonoxidation is still not inclusive Therefore this study wasplanned to compare two experimental design techniques andFenton oxidationwith four parameters such as [pollutants]iniDye Fe+2 H

2O2 Fe+2 and pH was selected as a case study

For comparison frequently used CCD and robust Taguchiexperimental design technique were chosen with a specialfocus on comparing the optimization and detailed statisticalanalysis of the experimental results

2 Background

21 Response Surface Methodology and Central CompositeDesign RSM a multivariate statistical tool consists of agroup of mathematical and statistical techniques that arebased on the fit of empirical models to the experimental

The Scientific World Journal 3

Analysis

Decision

Initial phase

Obtaining model equation

Comparing predicted and actual values

Model graphs (2D and 3D contour)

(significant)Lack of fitness (significant)

Optimization

Confirmation experiment

Selecting process factors and their levels

desirable

Conducting experiments

Selecting responses

ANOVA

Model selection

Or

Yes

Objective achieved

Evaluate the reason

No

Determining value of 120572 face centered value is

Adjusted andpredicted R

2 valueAdequate precision

(SN gt 4) F test

Figure 2 Central composite design flow diagram

data obtained in relation to experimental design [21] Itemploys lower order polynomial [22] and it has already beenproved to be a reliable statistical method for chemical processapplications [23 24]

In RSM category CCD which is appropriate for fittingsecond order polynomial equations has been frequentlydiscussed for optimizing several research problems A CCDhas three groups of design points [25]

(a) two-level factorial or fractional factorial design points(2119896) consisting of possible combinations of +1 and minus1levels of factor

(b) 2119896 axial points (sometimes called star points) fixedaxially at a distance say 120572 from the center to generatequadratic terms

(c) center points which represent replicate terms centerpoints provide a good and independent estimate ofthe experimental error

Considering these points the number of experimentsdesigned by CCD will be

119873 = 1198962 + 2119896 + 119899 (2)

where 119873 is the total number of experiments 119896 is thenumber of factors studied and 119899 is the number of replicatesCentral composite design under RSM is normally performedeither by using design expert software or Minitab In thisstudy design expert (Version 8071) is used as optimizationsoftware The steps that will be followed for the centralcomposite design (CCD) are presented in Figure 2

4 The Scientific World Journal

In CCD value of alpha is important to calculate as itcould determine the location of axial points in experimentaldomain Depending on alpha value design is sphericalorthogonal rotatable or face centered Practically it is inbetween face centered and spherical and is calculated as

120572 = (2119896)025

(3)

Value of alpha equals 1 is desirable because it ensures theposition of axial point within factorial portion region It iscalled face centered design and offers three levels for thefactors to be put in the experimental design matrix

Experimental results obtained are analyzed usingresponse surface regression procedure of statistical analysissystem Corelation between responses and independentvariables is obtained by fitting them into second orderpolynomial equation [10]

119884 = 1205730+119896

sum119894=1

120573119894119909119894+119896

sum119894=1

1205731198941198941199092119894119894+119896

sum119894=1

119896

sum119894 =119895=1

120573119894119895119909119894119909119895+ 120576 (4)

Here 119884 represents the responses 119896 is the total numberindependent factors 120573

0is an intercept 119894 119894119894 and 119894119895 with

120573 represent the coefficient values for linear quadratic andinteraction effects respectively and 119909

119894and 119909

119895in the above

equation show the coded levels for independent variables[26]

22 Taguchi Method and Signal to Noise Ratio Taguchimethod is a robust and multiparameter optimization statisti-cal technique which employs fewer numbers of experimentsto identify and optimize parameters to achieve desiredresponse [27 28] It is a simple and systematic way ofdetermining the effect of factors on responses and optimumcondition of the factors Taguchi method utilizes full frac-tional design called orthogonal arrays and ANOVA as a toolfor analysis [29] Orthogonal arrays are the minimum setof experiments which represents the various combinationsof factors Output of the orthogonal arrays is optimizedwith respect to signal to noise ratio (119878119873) of the responsesinstead of the responses itself and thus it reduces the processvariability [30] This feature marks the difference betweenthe conventional statistical technique and Taguchi methodThe stepwise procedure for Taguchi method is represented inFigure 3

In Taguchi method 119878119873 ratio is the measure of thedeviation of the response from the desired value Hereldquosignalrdquo implies the mean value while ldquonoiserdquo shows thestandard deviation term It means that lower variability inthe process is ensured through maximizing the 119878119873 ratioHowever depending on the type of response desired Taguchiclassified 119878119873 ratio into three categories smaller-the-betterlarger-the-better and nominal-the-better [31]

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (5)

Identifying factors and responses

Selecting suitable orthogonal array

Conducting experiments

ANOVA analysis

Determining optimum value

Confirming experiments

Transforming responses into SN ratios

Figure 3 Taguchi orthogonal array

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (6)

Larger is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1

1199102119894

) (7)

Nominal is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1205832

1205902) (8)

where 120583 = (1119899)sum119899119896=1119910119894 1205902 = (1(119899 minus 1))sum119899

119896=1(119910119894minus 120583)2

And 119910119894represents response variables and ldquo119899rdquo donates the

number of experimentsOne of the distinct features of Taguchi method is that

it determines optimum value in the form of 119878119873 ratio Thepredicted 119878119873 ratio at optimal process conditions can becomputed by the following mathematical equation [32]

119878119873predicted = 119878119873 +sum(119878119873119895minus 119878119873) (9)

where 119878119873 shows the mean of all 119878119873 ratios 119878119873119895is the

119878119873 ratio at the optimal level for each parameters and 119899 isthe number of process parameters that significantly affect theprocess

3 Case Study

In this study Fenton oxidation of synthetic dye acid blue113 has been taken as a case study for comparing twooptimization techniques that is CCD and Taguchi method

The Scientific World Journal 5

31 Experimental Details For performing Fenton oxidationall reagents used were of analytical grade and procured fromMerck Sdn Bhd Malaysia Synthetic dye acid blue 113 waspurchased from Sigma-Aldrich (M) Sdn Bhd Malaysia

For performing Fenton oxidation stock solutions of333 gL of H

2O2and 100 gL of FeSO

4sdot7H2O were prepared

All solutions were prepared by using distilled water Fentonoxidation experiments were performed in batch laboratoryscale Erlenmeyer flask (500mL capacity) equipped with amagnetic stirrer For each test 150mL of acid blue 113 dyesolution was placed into flask and pH was adjusted byusing 05M H

2SO4or 1M NaOH solution according to the

designed experiment Desired amounts of FeSO4sdot7H2O and

H2O2solutions were added to the dye solution respectively

while stirring at 150 rpm The start time was recorded whenH2O2solution was added After 90 minutes pH of the

solution was measured and sufficient amount of 1M NaOHsolution was added to increase pH above 11 to stop the reac-tion This is because in alkaline conditions Fe+2 precipitatesout as Fe+3 and H

2O2decomposes into oxygen Then after

2 hrs of settling time the supernatant was filtered through045 120583m Millipore filter and subjected to various analysesAll experiments were performed at room temperature andatmospheric pressure

32 Analysis pH measurements of the solution were carriedout with the aid of pH meter (CyberScan pH 300 Eutec-tic instruments) Quantitative measurement of the residualH2O2in treated wastewater was carried out by using per-

oxide test strips (Merck) The raw and treated samples werescanned using UV-spectrophotometer (Spectroquant Pharo300 Merck) And decolorization efficiency of the treatedsample was calculated as follows

Decolorization () = (1 minusAbs119891

Abs∘

) times 100 (10)

COD measurements were made according to the standardmethod (APHA AWWA and WFE 1998) For this CODtest cell supplied by Merck was heated in thermoreactor(Spectroquant TR 420) after adding required amount of thesample followed by the subsequent measurement in UV-spectrophotometer according to the standard method AndCOD removal efficiency is calculated as

COD () = (1 minusCOD119891

COD∘

) times 100 (11)

4 Result and Discussion

41 Central Composite Design All experiments for Fentonoxidation were designed according to RSM using centralcomposite design (CCD) with the aid of design expert(Version 8071) According to the literature review the mostimportant parameters which affect the efficiency of Fentonprocess are pH initial concentrations ofDye Fe+2 andH

2O2

[4 33 34] Therefore [Dye]ini pH H2O2 Fe+2 (wtwt) and

Dye Fe+2 (wtwt) ratios were chosen as control variables tobe optimized using CCD as given in Table 1

Table 1 Experimental range and levels of process variables

Independent numericalvariables Coded Low actual

valueHigh actual

valueDye (mgL) 119883

1100 300

H2O2 Fe+2 (wtwt) 119883

25 25

Dye Fe+2 (wtwt) 1198833

10 50pH 119883

42 9

Total 30 runs with 16 factorial 8 Axial and 6 centerpoints were suggested by design expert to optimize theresponses that is COD and decolorization efficiency Basedon the proposedmodel the following quadratic equation wasdeveloped to predict the dependent variables (responses) interms of independent variables and their interactions

119884 = 1198870+ 11988711199091+ 11988721199092+ 11988731199093+ 11988741199094+ 119887111199091

2 + 119887221199092

2

+ 119887331199093

2 + 11988741199094

2 + 1198871211990911199092+ 1198871311990911199093+ 1198871411990911199094

+ 1198872311990921199093+ 1198872411990921199094+ 1198873411990931199094

(12)

where 119884 is the response variable (COD removal or decol-orization efficiency) 119887

0is constant 119887

1 1198872 1198873 and 119887

4are

coefficient for linear effects 11988711 11988722 11988733 and 119887

44are quadratic

coefficient and 11988712 11988713 11988714 11988723 11988724 and 119887

34are interaction

coefficients [36] respectively

42 Model Results for Fenton Oxidation of Acid Blue 113

421 Model Fitting and Analysis of Variance (ANOVA)Different concentrations of CI acid blue dye 113 were pre-pared and Fenton oxidation was performed under differentconditions according to the experimental runs as suggestedby CCDmodel Based on experimental results the followingempirical second order polynomial equationswere developedshowing the interactions between the proposed independentvariables to obtain decolorization and COD removal efficien-cies

COD = 6418620 minus 020098 lowast (Dye) + 070063

lowast (H2O2 Fe+2) + 175866 lowast (Dye Fe+2)

lowast 042339 lowast (pH) + 348465119864 minus 003

lowast (Dye lowast Dye Fe+2) minus 174043119864003

lowast (Dye lowast Dye Fe+2) + 0013948 lowast (Dye lowast pH)

+ 0031013 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 013479 lowast (Dye Fe+2) lowast (pH)

+ 388643119864 minus 004 lowast (Dye2) minus 0066812

lowast (H2O2 (Fe+2)

2

) minus 0021456 lowast (Dye (Fe+2)2

)

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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RotatingMachinery

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

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Shock and Vibration

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Chemical EngineeringInternational Journal of Antennas and

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International Journal of

The Scientific World Journal 3

Analysis

Decision

Initial phase

Obtaining model equation

Comparing predicted and actual values

Model graphs (2D and 3D contour)

(significant)Lack of fitness (significant)

Optimization

Confirmation experiment

Selecting process factors and their levels

desirable

Conducting experiments

Selecting responses

ANOVA

Model selection

Or

Yes

Objective achieved

Evaluate the reason

No

Determining value of 120572 face centered value is

Adjusted andpredicted R

2 valueAdequate precision

(SN gt 4) F test

Figure 2 Central composite design flow diagram

data obtained in relation to experimental design [21] Itemploys lower order polynomial [22] and it has already beenproved to be a reliable statistical method for chemical processapplications [23 24]

In RSM category CCD which is appropriate for fittingsecond order polynomial equations has been frequentlydiscussed for optimizing several research problems A CCDhas three groups of design points [25]

(a) two-level factorial or fractional factorial design points(2119896) consisting of possible combinations of +1 and minus1levels of factor

(b) 2119896 axial points (sometimes called star points) fixedaxially at a distance say 120572 from the center to generatequadratic terms

(c) center points which represent replicate terms centerpoints provide a good and independent estimate ofthe experimental error

Considering these points the number of experimentsdesigned by CCD will be

119873 = 1198962 + 2119896 + 119899 (2)

where 119873 is the total number of experiments 119896 is thenumber of factors studied and 119899 is the number of replicatesCentral composite design under RSM is normally performedeither by using design expert software or Minitab In thisstudy design expert (Version 8071) is used as optimizationsoftware The steps that will be followed for the centralcomposite design (CCD) are presented in Figure 2

4 The Scientific World Journal

In CCD value of alpha is important to calculate as itcould determine the location of axial points in experimentaldomain Depending on alpha value design is sphericalorthogonal rotatable or face centered Practically it is inbetween face centered and spherical and is calculated as

120572 = (2119896)025

(3)

Value of alpha equals 1 is desirable because it ensures theposition of axial point within factorial portion region It iscalled face centered design and offers three levels for thefactors to be put in the experimental design matrix

Experimental results obtained are analyzed usingresponse surface regression procedure of statistical analysissystem Corelation between responses and independentvariables is obtained by fitting them into second orderpolynomial equation [10]

119884 = 1205730+119896

sum119894=1

120573119894119909119894+119896

sum119894=1

1205731198941198941199092119894119894+119896

sum119894=1

119896

sum119894 =119895=1

120573119894119895119909119894119909119895+ 120576 (4)

Here 119884 represents the responses 119896 is the total numberindependent factors 120573

0is an intercept 119894 119894119894 and 119894119895 with

120573 represent the coefficient values for linear quadratic andinteraction effects respectively and 119909

119894and 119909

119895in the above

equation show the coded levels for independent variables[26]

22 Taguchi Method and Signal to Noise Ratio Taguchimethod is a robust and multiparameter optimization statisti-cal technique which employs fewer numbers of experimentsto identify and optimize parameters to achieve desiredresponse [27 28] It is a simple and systematic way ofdetermining the effect of factors on responses and optimumcondition of the factors Taguchi method utilizes full frac-tional design called orthogonal arrays and ANOVA as a toolfor analysis [29] Orthogonal arrays are the minimum setof experiments which represents the various combinationsof factors Output of the orthogonal arrays is optimizedwith respect to signal to noise ratio (119878119873) of the responsesinstead of the responses itself and thus it reduces the processvariability [30] This feature marks the difference betweenthe conventional statistical technique and Taguchi methodThe stepwise procedure for Taguchi method is represented inFigure 3

In Taguchi method 119878119873 ratio is the measure of thedeviation of the response from the desired value Hereldquosignalrdquo implies the mean value while ldquonoiserdquo shows thestandard deviation term It means that lower variability inthe process is ensured through maximizing the 119878119873 ratioHowever depending on the type of response desired Taguchiclassified 119878119873 ratio into three categories smaller-the-betterlarger-the-better and nominal-the-better [31]

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (5)

Identifying factors and responses

Selecting suitable orthogonal array

Conducting experiments

ANOVA analysis

Determining optimum value

Confirming experiments

Transforming responses into SN ratios

Figure 3 Taguchi orthogonal array

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (6)

Larger is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1

1199102119894

) (7)

Nominal is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1205832

1205902) (8)

where 120583 = (1119899)sum119899119896=1119910119894 1205902 = (1(119899 minus 1))sum119899

119896=1(119910119894minus 120583)2

And 119910119894represents response variables and ldquo119899rdquo donates the

number of experimentsOne of the distinct features of Taguchi method is that

it determines optimum value in the form of 119878119873 ratio Thepredicted 119878119873 ratio at optimal process conditions can becomputed by the following mathematical equation [32]

119878119873predicted = 119878119873 +sum(119878119873119895minus 119878119873) (9)

where 119878119873 shows the mean of all 119878119873 ratios 119878119873119895is the

119878119873 ratio at the optimal level for each parameters and 119899 isthe number of process parameters that significantly affect theprocess

3 Case Study

In this study Fenton oxidation of synthetic dye acid blue113 has been taken as a case study for comparing twooptimization techniques that is CCD and Taguchi method

The Scientific World Journal 5

31 Experimental Details For performing Fenton oxidationall reagents used were of analytical grade and procured fromMerck Sdn Bhd Malaysia Synthetic dye acid blue 113 waspurchased from Sigma-Aldrich (M) Sdn Bhd Malaysia

For performing Fenton oxidation stock solutions of333 gL of H

2O2and 100 gL of FeSO

4sdot7H2O were prepared

All solutions were prepared by using distilled water Fentonoxidation experiments were performed in batch laboratoryscale Erlenmeyer flask (500mL capacity) equipped with amagnetic stirrer For each test 150mL of acid blue 113 dyesolution was placed into flask and pH was adjusted byusing 05M H

2SO4or 1M NaOH solution according to the

designed experiment Desired amounts of FeSO4sdot7H2O and

H2O2solutions were added to the dye solution respectively

while stirring at 150 rpm The start time was recorded whenH2O2solution was added After 90 minutes pH of the

solution was measured and sufficient amount of 1M NaOHsolution was added to increase pH above 11 to stop the reac-tion This is because in alkaline conditions Fe+2 precipitatesout as Fe+3 and H

2O2decomposes into oxygen Then after

2 hrs of settling time the supernatant was filtered through045 120583m Millipore filter and subjected to various analysesAll experiments were performed at room temperature andatmospheric pressure

32 Analysis pH measurements of the solution were carriedout with the aid of pH meter (CyberScan pH 300 Eutec-tic instruments) Quantitative measurement of the residualH2O2in treated wastewater was carried out by using per-

oxide test strips (Merck) The raw and treated samples werescanned using UV-spectrophotometer (Spectroquant Pharo300 Merck) And decolorization efficiency of the treatedsample was calculated as follows

Decolorization () = (1 minusAbs119891

Abs∘

) times 100 (10)

COD measurements were made according to the standardmethod (APHA AWWA and WFE 1998) For this CODtest cell supplied by Merck was heated in thermoreactor(Spectroquant TR 420) after adding required amount of thesample followed by the subsequent measurement in UV-spectrophotometer according to the standard method AndCOD removal efficiency is calculated as

COD () = (1 minusCOD119891

COD∘

) times 100 (11)

4 Result and Discussion

41 Central Composite Design All experiments for Fentonoxidation were designed according to RSM using centralcomposite design (CCD) with the aid of design expert(Version 8071) According to the literature review the mostimportant parameters which affect the efficiency of Fentonprocess are pH initial concentrations ofDye Fe+2 andH

2O2

[4 33 34] Therefore [Dye]ini pH H2O2 Fe+2 (wtwt) and

Dye Fe+2 (wtwt) ratios were chosen as control variables tobe optimized using CCD as given in Table 1

Table 1 Experimental range and levels of process variables

Independent numericalvariables Coded Low actual

valueHigh actual

valueDye (mgL) 119883

1100 300

H2O2 Fe+2 (wtwt) 119883

25 25

Dye Fe+2 (wtwt) 1198833

10 50pH 119883

42 9

Total 30 runs with 16 factorial 8 Axial and 6 centerpoints were suggested by design expert to optimize theresponses that is COD and decolorization efficiency Basedon the proposedmodel the following quadratic equation wasdeveloped to predict the dependent variables (responses) interms of independent variables and their interactions

119884 = 1198870+ 11988711199091+ 11988721199092+ 11988731199093+ 11988741199094+ 119887111199091

2 + 119887221199092

2

+ 119887331199093

2 + 11988741199094

2 + 1198871211990911199092+ 1198871311990911199093+ 1198871411990911199094

+ 1198872311990921199093+ 1198872411990921199094+ 1198873411990931199094

(12)

where 119884 is the response variable (COD removal or decol-orization efficiency) 119887

0is constant 119887

1 1198872 1198873 and 119887

4are

coefficient for linear effects 11988711 11988722 11988733 and 119887

44are quadratic

coefficient and 11988712 11988713 11988714 11988723 11988724 and 119887

34are interaction

coefficients [36] respectively

42 Model Results for Fenton Oxidation of Acid Blue 113

421 Model Fitting and Analysis of Variance (ANOVA)Different concentrations of CI acid blue dye 113 were pre-pared and Fenton oxidation was performed under differentconditions according to the experimental runs as suggestedby CCDmodel Based on experimental results the followingempirical second order polynomial equationswere developedshowing the interactions between the proposed independentvariables to obtain decolorization and COD removal efficien-cies

COD = 6418620 minus 020098 lowast (Dye) + 070063

lowast (H2O2 Fe+2) + 175866 lowast (Dye Fe+2)

lowast 042339 lowast (pH) + 348465119864 minus 003

lowast (Dye lowast Dye Fe+2) minus 174043119864003

lowast (Dye lowast Dye Fe+2) + 0013948 lowast (Dye lowast pH)

+ 0031013 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 013479 lowast (Dye Fe+2) lowast (pH)

+ 388643119864 minus 004 lowast (Dye2) minus 0066812

lowast (H2O2 (Fe+2)

2

) minus 0021456 lowast (Dye (Fe+2)2

)

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

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International Journal of

4 The Scientific World Journal

In CCD value of alpha is important to calculate as itcould determine the location of axial points in experimentaldomain Depending on alpha value design is sphericalorthogonal rotatable or face centered Practically it is inbetween face centered and spherical and is calculated as

120572 = (2119896)025

(3)

Value of alpha equals 1 is desirable because it ensures theposition of axial point within factorial portion region It iscalled face centered design and offers three levels for thefactors to be put in the experimental design matrix

Experimental results obtained are analyzed usingresponse surface regression procedure of statistical analysissystem Corelation between responses and independentvariables is obtained by fitting them into second orderpolynomial equation [10]

119884 = 1205730+119896

sum119894=1

120573119894119909119894+119896

sum119894=1

1205731198941198941199092119894119894+119896

sum119894=1

119896

sum119894 =119895=1

120573119894119895119909119894119909119895+ 120576 (4)

Here 119884 represents the responses 119896 is the total numberindependent factors 120573

0is an intercept 119894 119894119894 and 119894119895 with

120573 represent the coefficient values for linear quadratic andinteraction effects respectively and 119909

119894and 119909

119895in the above

equation show the coded levels for independent variables[26]

22 Taguchi Method and Signal to Noise Ratio Taguchimethod is a robust and multiparameter optimization statisti-cal technique which employs fewer numbers of experimentsto identify and optimize parameters to achieve desiredresponse [27 28] It is a simple and systematic way ofdetermining the effect of factors on responses and optimumcondition of the factors Taguchi method utilizes full frac-tional design called orthogonal arrays and ANOVA as a toolfor analysis [29] Orthogonal arrays are the minimum setof experiments which represents the various combinationsof factors Output of the orthogonal arrays is optimizedwith respect to signal to noise ratio (119878119873) of the responsesinstead of the responses itself and thus it reduces the processvariability [30] This feature marks the difference betweenthe conventional statistical technique and Taguchi methodThe stepwise procedure for Taguchi method is represented inFigure 3

In Taguchi method 119878119873 ratio is the measure of thedeviation of the response from the desired value Hereldquosignalrdquo implies the mean value while ldquonoiserdquo shows thestandard deviation term It means that lower variability inthe process is ensured through maximizing the 119878119873 ratioHowever depending on the type of response desired Taguchiclassified 119878119873 ratio into three categories smaller-the-betterlarger-the-better and nominal-the-better [31]

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (5)

Identifying factors and responses

Selecting suitable orthogonal array

Conducting experiments

ANOVA analysis

Determining optimum value

Confirming experiments

Transforming responses into SN ratios

Figure 3 Taguchi orthogonal array

Smaller is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1199102119894) (6)

Larger is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1

1199102119894

) (7)

Nominal is better

119878119873 = minus10 log(1119899

119899

sum119896=1

1205832

1205902) (8)

where 120583 = (1119899)sum119899119896=1119910119894 1205902 = (1(119899 minus 1))sum119899

119896=1(119910119894minus 120583)2

And 119910119894represents response variables and ldquo119899rdquo donates the

number of experimentsOne of the distinct features of Taguchi method is that

it determines optimum value in the form of 119878119873 ratio Thepredicted 119878119873 ratio at optimal process conditions can becomputed by the following mathematical equation [32]

119878119873predicted = 119878119873 +sum(119878119873119895minus 119878119873) (9)

where 119878119873 shows the mean of all 119878119873 ratios 119878119873119895is the

119878119873 ratio at the optimal level for each parameters and 119899 isthe number of process parameters that significantly affect theprocess

3 Case Study

In this study Fenton oxidation of synthetic dye acid blue113 has been taken as a case study for comparing twooptimization techniques that is CCD and Taguchi method

The Scientific World Journal 5

31 Experimental Details For performing Fenton oxidationall reagents used were of analytical grade and procured fromMerck Sdn Bhd Malaysia Synthetic dye acid blue 113 waspurchased from Sigma-Aldrich (M) Sdn Bhd Malaysia

For performing Fenton oxidation stock solutions of333 gL of H

2O2and 100 gL of FeSO

4sdot7H2O were prepared

All solutions were prepared by using distilled water Fentonoxidation experiments were performed in batch laboratoryscale Erlenmeyer flask (500mL capacity) equipped with amagnetic stirrer For each test 150mL of acid blue 113 dyesolution was placed into flask and pH was adjusted byusing 05M H

2SO4or 1M NaOH solution according to the

designed experiment Desired amounts of FeSO4sdot7H2O and

H2O2solutions were added to the dye solution respectively

while stirring at 150 rpm The start time was recorded whenH2O2solution was added After 90 minutes pH of the

solution was measured and sufficient amount of 1M NaOHsolution was added to increase pH above 11 to stop the reac-tion This is because in alkaline conditions Fe+2 precipitatesout as Fe+3 and H

2O2decomposes into oxygen Then after

2 hrs of settling time the supernatant was filtered through045 120583m Millipore filter and subjected to various analysesAll experiments were performed at room temperature andatmospheric pressure

32 Analysis pH measurements of the solution were carriedout with the aid of pH meter (CyberScan pH 300 Eutec-tic instruments) Quantitative measurement of the residualH2O2in treated wastewater was carried out by using per-

oxide test strips (Merck) The raw and treated samples werescanned using UV-spectrophotometer (Spectroquant Pharo300 Merck) And decolorization efficiency of the treatedsample was calculated as follows

Decolorization () = (1 minusAbs119891

Abs∘

) times 100 (10)

COD measurements were made according to the standardmethod (APHA AWWA and WFE 1998) For this CODtest cell supplied by Merck was heated in thermoreactor(Spectroquant TR 420) after adding required amount of thesample followed by the subsequent measurement in UV-spectrophotometer according to the standard method AndCOD removal efficiency is calculated as

COD () = (1 minusCOD119891

COD∘

) times 100 (11)

4 Result and Discussion

41 Central Composite Design All experiments for Fentonoxidation were designed according to RSM using centralcomposite design (CCD) with the aid of design expert(Version 8071) According to the literature review the mostimportant parameters which affect the efficiency of Fentonprocess are pH initial concentrations ofDye Fe+2 andH

2O2

[4 33 34] Therefore [Dye]ini pH H2O2 Fe+2 (wtwt) and

Dye Fe+2 (wtwt) ratios were chosen as control variables tobe optimized using CCD as given in Table 1

Table 1 Experimental range and levels of process variables

Independent numericalvariables Coded Low actual

valueHigh actual

valueDye (mgL) 119883

1100 300

H2O2 Fe+2 (wtwt) 119883

25 25

Dye Fe+2 (wtwt) 1198833

10 50pH 119883

42 9

Total 30 runs with 16 factorial 8 Axial and 6 centerpoints were suggested by design expert to optimize theresponses that is COD and decolorization efficiency Basedon the proposedmodel the following quadratic equation wasdeveloped to predict the dependent variables (responses) interms of independent variables and their interactions

119884 = 1198870+ 11988711199091+ 11988721199092+ 11988731199093+ 11988741199094+ 119887111199091

2 + 119887221199092

2

+ 119887331199093

2 + 11988741199094

2 + 1198871211990911199092+ 1198871311990911199093+ 1198871411990911199094

+ 1198872311990921199093+ 1198872411990921199094+ 1198873411990931199094

(12)

where 119884 is the response variable (COD removal or decol-orization efficiency) 119887

0is constant 119887

1 1198872 1198873 and 119887

4are

coefficient for linear effects 11988711 11988722 11988733 and 119887

44are quadratic

coefficient and 11988712 11988713 11988714 11988723 11988724 and 119887

34are interaction

coefficients [36] respectively

42 Model Results for Fenton Oxidation of Acid Blue 113

421 Model Fitting and Analysis of Variance (ANOVA)Different concentrations of CI acid blue dye 113 were pre-pared and Fenton oxidation was performed under differentconditions according to the experimental runs as suggestedby CCDmodel Based on experimental results the followingempirical second order polynomial equationswere developedshowing the interactions between the proposed independentvariables to obtain decolorization and COD removal efficien-cies

COD = 6418620 minus 020098 lowast (Dye) + 070063

lowast (H2O2 Fe+2) + 175866 lowast (Dye Fe+2)

lowast 042339 lowast (pH) + 348465119864 minus 003

lowast (Dye lowast Dye Fe+2) minus 174043119864003

lowast (Dye lowast Dye Fe+2) + 0013948 lowast (Dye lowast pH)

+ 0031013 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 013479 lowast (Dye Fe+2) lowast (pH)

+ 388643119864 minus 004 lowast (Dye2) minus 0066812

lowast (H2O2 (Fe+2)

2

) minus 0021456 lowast (Dye (Fe+2)2

)

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

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The Scientific World Journal 5

31 Experimental Details For performing Fenton oxidationall reagents used were of analytical grade and procured fromMerck Sdn Bhd Malaysia Synthetic dye acid blue 113 waspurchased from Sigma-Aldrich (M) Sdn Bhd Malaysia

For performing Fenton oxidation stock solutions of333 gL of H

2O2and 100 gL of FeSO

4sdot7H2O were prepared

All solutions were prepared by using distilled water Fentonoxidation experiments were performed in batch laboratoryscale Erlenmeyer flask (500mL capacity) equipped with amagnetic stirrer For each test 150mL of acid blue 113 dyesolution was placed into flask and pH was adjusted byusing 05M H

2SO4or 1M NaOH solution according to the

designed experiment Desired amounts of FeSO4sdot7H2O and

H2O2solutions were added to the dye solution respectively

while stirring at 150 rpm The start time was recorded whenH2O2solution was added After 90 minutes pH of the

solution was measured and sufficient amount of 1M NaOHsolution was added to increase pH above 11 to stop the reac-tion This is because in alkaline conditions Fe+2 precipitatesout as Fe+3 and H

2O2decomposes into oxygen Then after

2 hrs of settling time the supernatant was filtered through045 120583m Millipore filter and subjected to various analysesAll experiments were performed at room temperature andatmospheric pressure

32 Analysis pH measurements of the solution were carriedout with the aid of pH meter (CyberScan pH 300 Eutec-tic instruments) Quantitative measurement of the residualH2O2in treated wastewater was carried out by using per-

oxide test strips (Merck) The raw and treated samples werescanned using UV-spectrophotometer (Spectroquant Pharo300 Merck) And decolorization efficiency of the treatedsample was calculated as follows

Decolorization () = (1 minusAbs119891

Abs∘

) times 100 (10)

COD measurements were made according to the standardmethod (APHA AWWA and WFE 1998) For this CODtest cell supplied by Merck was heated in thermoreactor(Spectroquant TR 420) after adding required amount of thesample followed by the subsequent measurement in UV-spectrophotometer according to the standard method AndCOD removal efficiency is calculated as

COD () = (1 minusCOD119891

COD∘

) times 100 (11)

4 Result and Discussion

41 Central Composite Design All experiments for Fentonoxidation were designed according to RSM using centralcomposite design (CCD) with the aid of design expert(Version 8071) According to the literature review the mostimportant parameters which affect the efficiency of Fentonprocess are pH initial concentrations ofDye Fe+2 andH

2O2

[4 33 34] Therefore [Dye]ini pH H2O2 Fe+2 (wtwt) and

Dye Fe+2 (wtwt) ratios were chosen as control variables tobe optimized using CCD as given in Table 1

Table 1 Experimental range and levels of process variables

Independent numericalvariables Coded Low actual

valueHigh actual

valueDye (mgL) 119883

1100 300

H2O2 Fe+2 (wtwt) 119883

25 25

Dye Fe+2 (wtwt) 1198833

10 50pH 119883

42 9

Total 30 runs with 16 factorial 8 Axial and 6 centerpoints were suggested by design expert to optimize theresponses that is COD and decolorization efficiency Basedon the proposedmodel the following quadratic equation wasdeveloped to predict the dependent variables (responses) interms of independent variables and their interactions

119884 = 1198870+ 11988711199091+ 11988721199092+ 11988731199093+ 11988741199094+ 119887111199091

2 + 119887221199092

2

+ 119887331199093

2 + 11988741199094

2 + 1198871211990911199092+ 1198871311990911199093+ 1198871411990911199094

+ 1198872311990921199093+ 1198872411990921199094+ 1198873411990931199094

(12)

where 119884 is the response variable (COD removal or decol-orization efficiency) 119887

0is constant 119887

1 1198872 1198873 and 119887

4are

coefficient for linear effects 11988711 11988722 11988733 and 119887

44are quadratic

coefficient and 11988712 11988713 11988714 11988723 11988724 and 119887

34are interaction

coefficients [36] respectively

42 Model Results for Fenton Oxidation of Acid Blue 113

421 Model Fitting and Analysis of Variance (ANOVA)Different concentrations of CI acid blue dye 113 were pre-pared and Fenton oxidation was performed under differentconditions according to the experimental runs as suggestedby CCDmodel Based on experimental results the followingempirical second order polynomial equationswere developedshowing the interactions between the proposed independentvariables to obtain decolorization and COD removal efficien-cies

COD = 6418620 minus 020098 lowast (Dye) + 070063

lowast (H2O2 Fe+2) + 175866 lowast (Dye Fe+2)

lowast 042339 lowast (pH) + 348465119864 minus 003

lowast (Dye lowast Dye Fe+2) minus 174043119864003

lowast (Dye lowast Dye Fe+2) + 0013948 lowast (Dye lowast pH)

+ 0031013 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 013479 lowast (Dye Fe+2) lowast (pH)

+ 388643119864 minus 004 lowast (Dye2) minus 0066812

lowast (H2O2 (Fe+2)

2

) minus 0021456 lowast (Dye (Fe+2)2

)

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

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Electrical and Computer Engineering

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Advances inOptoElectronics

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Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

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Navigation and Observation

International Journal of

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DistributedSensor Networks

International Journal of

6 The Scientific World Journal

Table 2 Experimental design matrix experimental runs and predicted values on COD removal and decolorization efficiency

Independent variables (119883) Dependent variables (119884 ())Actual values Predicted values

Run Dye (mgL) H2O2 Fe+2 (wtwt) Dye Fe+2 (wtwt) pH COD () Decolorization () COD () Decolorization ()

1 200 15 30 55 753 954 732 9512 200 15 30 55 764 954 732 9513 300 25 50 9 628 968 609 9574 200 25 30 55 734 981 698 9755 300 5 50 9 348 800 351 7986 200 15 30 55 734 955 732 9517 100 5 10 9 665 558 634 5978 100 25 50 2 877 992 853 10009 200 15 30 9 658 789 673 80310 300 15 30 55 783 945 802 98611 100 15 30 55 771 901 739 86712 100 5 10 2 670 934 661 92213 100 5 50 9 302 561 329 54414 200 15 30 55 745 954 732 95115 300 5 10 9 779 891 794 85916 200 5 30 55 608 843 633 85617 100 25 10 9 480 679 5051 65118 200 15 30 55 703 946 7320 95119 300 25 10 2 674 989 636 98320 300 5 10 2 614 952 625 95621 100 25 10 2 503 976 531 99922 200 15 10 55 677 982 677 97723 300 25 10 9 804 844 805 86324 300 25 50 2 755 994 818 97725 200 15 30 2 741 983 791 97526 100 25 50 9 447 736 449 75427 200 15 50 55 627 935 616 94728 200 15 30 55 734 966 732 95129 100 5 50 2 721 765 734 76730 300 5 50 2 612 789 559 794

Decolorization

= 8585276 + 0092035 lowast (Dye) + 143440

lowast (H2O2 Fe+2) minus 070074 lowast (Dye Fe+2)

minus 097745 lowast pH minus 126375119864 minus 003

lowast (Dye lowastH2O2 Fe+2) minus 101250119864 minus 004

lowast (Dye lowast Dye Fe+2) + 0016293 lowast (Dye lowast pH)

+ 0019450 lowast (H2O2 Fe+2) lowast (Dye Fe+2)

minus 0016857 lowast (H2O2 Fe+2) lowast (pH) + 0036054

lowast (Dye Fe+2) lowast (pH) minus 250533119864 minus 004

lowast (Dye2) minus 0036003 lowast (H2O2 (Fe+2)

2

)

minus 050615 lowast (pH2) (13)

The objective of this empirical model was to adequatelydescribe the interaction of factors influencing the process effi-ciency at the concentration ranges investigated Experimentaland predicted values on COD removal and decolorizationefficiencies are provided in Table 2 The observed CODremoval and decolorization values vary between 302ndash877and 561ndash9923 which are in good agreement with thepredicted values as shown in Figure 4

Mathematical equation developed after fitting the func-tion to the data may give misleading results and cannotdescribe the domain of the model adequately [37] That is

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

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Control Scienceand Engineering

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Submit your manuscripts athttpwwwhindawicom

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Chemical EngineeringInternational Journal of Antennas and

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DistributedSensor Networks

International Journal of

The Scientific World Journal 7

Actual

Pred

icte

d

3000

4000

5000

6000

7000

8000

9000

3000 4000 5000 6000 7000 8000 9000

(a)

Actual

Pred

icte

d

5000

6000

7000

8000

9000

10000

11000

5000 6000 7000 8000 9000 10000 11000

(b)

Figure 4 Predicted and actual value for (a) COD and (b) decolorization efficiency

Table 3 ANOVA results for CCD

Source Sum of squares Degree of freedom Mean square 119865 value Prob gt 119865COD removal

Model 490221 12 40852 3241 lt00001(significant)

Dye 17373 1 17373 3241 00017H2O2 Fe

+2 18848 1 18848 1394 00012Dye Fe+2 16836 1 16836 1495 0002pH 62039 1 62039 1336 lt00001

Color Removal

Model 431088 14 30792 4973 lt00001(significant)

Dye 63594 1 63594 10270 lt00001H2O2 Fe

+2 63155 1 63155 102 lt00001Dye Fe+2 3890 1 3890 628 00242pH 133197 1 133197 21512 lt00001

why ANOVA is an integral part of the data analysis and is themore reliable way to evaluate the quality of the model fitted[21] Table 3 shows the analysis of variance for COD and colorremoval efficiency

Values of Prob gt 119865 less than 00500 imply that the modelterms are significant while values greater than 01000 aredemonstrated as insignificant for the regressionmodel In thecurrent study 119865 values 3241 and 4973 for COD and colorremoval denote the model as significantThe goodness of thefit of the model is also checked by 1198772 value In both cases thevalues for this regression coefficient were 09789 and 09581which implies that this model is statistically significant andis in reasonable agreement with the adjusted 1198772 MoreoverldquoAdeq precisionrdquo is used to determine the signal to noise(119878119873) ratio to determine the validity of the model A ratiogreater than 4 is recommended In our case 119878119873 valuesof 259 and 223 for color and COD removal indicate anadequate signalThey also show that thismodel can be used tonavigate the design space Another checkpoint for validating

the experimental data is the analysis of normal probabilityplots The normal probability plot indicates whether theresiduals follow a normal distribution in which case thepoints will follow a straight line as it is in the current study(Figures A1 and A2 in Supplementary Material availableonline at httpdxdoiorg1011552014869120) Consideringthe above explained ANOVA results it can be concludedthat this model explained the Fenton reaction and can beemployed to navigate the design space in terms of decoloriza-tion and COD removal efficiencies

422 Response Surface Plotting andOptimization ofOperatingParameters Graphical interpretation of interactions by usingthree and two dimensional plots of regressionmodel is highlyrecommended and is used to assess the interactive effectsbetween the process variables and treatment efficiencies ofFenton process [38ndash40] The surface response plots of CODand color removal efficiencies of Fenton reaction regardinginteraction effects between dye concentration and other

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

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Control Scienceand Engineering

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DistributedSensor Networks

International Journal of

8 The Scientific World Journal

Table4Interactionof

operatingparametersfor

CODremovaleffi

ciency

COD(

)

Effects

Dye

(mgL)

Dye

Fe+

2

(wtw

t)H

2O2Fe+

2

(wtw

t)pH

COD(

)Re

ason

Effecto

fDye

Fe+

2ratio

(FigureA

4)

100

10ndash23

153

65ndash725(in

creased)

Atlowdyec

oncentratio

nsincreaseinDye

Fe+

2(w

twt)results

inad

ecreasein

Fe+2concentrationandincrease

inH

2O2additio

n(H

2O2Fe+

2 )which

increases

thep

rodu

ctionof

HO∙

radicalfor

dyed

egradatio

n

35ndash50

153

72ndash6

5(decreased)

Scavenging

ofHO∙

radicalbyH

2O2atlowconcentrations

ofFe

+2andhigh

concentrations

ofH

2O2[3]

250ndash

300

10ndash25

153

80(in

creased)

Optim

umam

ountso

fH2O

2andFe

+2resultin

thep

rodu

ctionof

HO∙

radical

adequateenou

ghform

axim

umdyed

egradatio

n

Effecto

fH2O

2Fe+

2

ratio

(FigureA

5)

100

305ndash10

370ndash72

100ndash

150

305

373ndash6

8(decreased)

Lessavailabilityof

HO∙

100

3020ndash25

373ndash6

8(decreased)

Scavenging

ofHO∙

radicalbyexcessam

ount

ofH

2O2

300

3010ndash25

374ndash80(in

creased)

CODremovaleffi

ciency

increasesfrom

74to

80becauseo

fthe

prop

ortio

nate

amou

ntof

HO∙

radicalprodu

ction

pH100ndash

300

10ndash50

5ndash25

380

80CO

Dremovaleffi

ciency

becauseo

fthe

availabilityof

Fe+2andH

2O2in

aqueou

smedium

(optim

umcond

ition

sofo

ther

varia

bles)

(FigureA

6)

100ndash

300

10ndash50

5ndash25

960

Decom

positionof

H2O

2to

H2O

andO

2atpH

above4

[3]

Deactivationof

ferrou

scatalystw

iththeformationof

ferrichydroxocom

plex

[35]

The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Control Scienceand Engineering

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The Scientific World Journal 9

Table 5 Optimized operating parameters

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Predicted responses

COD () Decolorization () Desirability300 2592 1915 3 8164 9940 0972

selected independent variables are presented in supplemen-tary data in Figures A3ndashA6

The interaction for assessing decolorization efficiencyimplies that DyeFe+2 and H

2O2Fe+2 have proportional

effect on color removal efficiency It can be seen from theplots that there is an increase in decolorization efficiencywith increase in control variables and dye concentrationThe reason for this increasing trend is that HO∙ radicallyproduced is reactive enough for the cleavage of theAzo bonds(ndashN=Nndash) and at high values of H

2O2Fe+2 and DyeFe+2

higher concentrations of HO∙ radical are available to reactwith the high concentration of dye [33] In this study 95decolorization of acid blue dye was observed within 10minutes of reaction time under optimum conditions Andover 90 of the color removal was observed for most of thetreated samples However from data available in Table 2 andcontour plots (Figure A3) it was found that pH exhibitsinverse relationship with dye decolorization efficiencyThis isbecause at higher pH values decomposition of H

2O2to oxy-

gen and conversion of ferrous ions to ferric hydroxocomplextake place which will in turn make HO∙ radical unavailablefor the reaction to take place [41]

From aforementioned discussion it is confirmed thatFentonrsquos reagents are active for decolorization Howeverefficient degradation of dye is difficult to achieve and itrequires optimization of the Fenton oxidation Unlike decol-orization concentration of Fentonrsquos reagents is not directlylinked with COD removal efficiency In order to make thingsunderstandable and comparable a detailed analysis of theeffect of Fentonrsquos reagent on COD removal efficiency ispresented in Table 4 Moreover three- and two-dimensionalcontour plots obtained by CCD model are also provided insupplementary data (Figures A4ndashA6)

Optimization study of the experimental results wasperformed by keeping all responses within desired rangesby using response surface methodology In present studiesdye concentration was targeted to the maximum and othervariables were kept in range Based on the suggested valuesas given in Table 5 experiment was conducted to validate theoptimized results According to the results obtained approxi-mately 791 of the COD removal was achievedwith 98401decolorization efficiency This indicates a good agreementof the experimental and predicted results under optimizedconditions Comparison of the results with previously con-ducted studies indicates that efficiency of the process isimproved in terms of both chemical consumptions and CODremoval efficiency For example Meric et al [42] obtained71 COD and 99 color removal at optimum conditionsof 100mgL of FeSO

4and 400mgL of H

2O2for 100mgL

of Reactive Black 5 In another study 2000mgL of H2O2

and 200mgL of FeSO4were used for 88 COD removal of

200mgL of Reactive Black 5 [43] It implies that CCD under

Table 6 Factors and levels of orthogonal array

Parameters Level 1 Level 2 Level 3[Dye] 100 200 300Dye Fe+2 10 30 50H2O2 Fe

+2 5 15 25pH 2 55 9

RSM is a suitable tool for optimizing Fenton treatment ofthe recalcitrant wastewater with improved efficiency and lessconsumption of chemicals

5 Taguchi Method

51 Experimental Design Taguchi method was used to deter-mine the optimum conditions for Fenton oxidation andto make comparison with the results obtained with CCDMinitab 16 was used for the orthogonal experimental designSame as before [Dye]ini DyeFe+2 (wtwt) H

2O2Fe+2

(wtwt) and pH were chosen as control factors for opti-mization through Taguchi orthogonal arrays experimentaldesign Each factor was varied at three levels (Table 6) and1198719orthogonal array was selected to determine the optimal

conditions with minimum number of experiments Thenumber of experiments required was reduced to 9 which wasconsiderably lesser than that of CCD It implies that only9 experiments with different combination of parameters arerequired to study Fenton oxidation which in conventionalfull factorial design would be 34 = 81 experimental runs

In second stage experiments were performed andresponse values were obtained For result analysis Taguchimethod follows entirely different steps in contrast to CCD Asfollowed by previous studies response values were convertedinto 119878119873 ratio which was used to analyze the results [1819 44ndash46] For Fenton oxidation maximum COD and colorremoval percentages are desired that is why ldquolarger is betterrdquo119878119873 ratio formula as given by (3) was used to determine the119878119873 value for each response The experimental results and119878119873 ratio for each run are given in Table 7

In comparison to CCD ranking of operating parametersin terms of contribution to response values is possible withTaguchi method It also suggests the use of Taguchi methodfor screening the input variables during the initial stages ofprocess investigation In the current study four parameterswere selected and from Table 8 it is clear that for bothtypes of responses pH was the most contributing factorThis observation was also confirmed from the literature thatFenton oxidation shows maximum efficiency at pH 3 anddeviation from this value decreases the efficiency of theprocess [41]

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

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Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

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RotatingMachinery

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

Propagation

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Navigation and Observation

International Journal of

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DistributedSensor Networks

International Journal of

10 The Scientific World Journal

Table 7 1198719orthogonal designs Levels of four factors and experimental results obtained

Dye (mgL) Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH Actual values 119878119873 ratio

COD () Decolorization () COD Decolorization1 1 1 1 748603 989496 3653 39901 2 2 2 530726 979920 3450 39821 3 3 3 363128 895582 3267 39042 1 2 3 326996 836843 3097 38452 2 3 1 809886 991548 3792 39922 3 1 2 429658 938547 2850 39453 1 3 2 690217 997837 3678 39983 2 1 3 347826 948740 3062 39543 3 2 1 578804 998905 3525 3999

Table 8 Response table for signal to noise (119878119873) ratio

Level Dye Dye Fe+2 (wtwt) H2O2 Fe+2 (wtwt) pH

COD removal1 3472 3506 3387 37962 3384 3475 3412 34773 3494 3369 3552 3077Delta 110 137 165 719Rank 4 3 2 1Decolorization1 3959 3945 3963 39942 3928 3976 3942 39753 3984 3949 3965 3901Delta 056 032 023 093Rank 2 3 4 1

52 Statistical Analysis In CCD analysis of variance(ANOVA) and regression models are used as evaluationcriteria for the statistical analysis of the results HoweverTaguchi method uses signal to noise ratio (119878119873) as a mainapproach for the analysis Nevertheless ANOVA can beemployed for the evaluation of experimental results witha main objective of determining the contribution of eachfactor to variance of result It is similar to regression analysiswhich is used to study and model the relationship betweenresponse and one or more independent variables [47]

Table 9 shows ANOVA results for both COD and colorremoval efficiency of acid blue 113 dye From the table it isclear that pH exhibits maximum contribution with percentcontribution of 662 and 8762 for both color and CODremoval respectively It is also in agreement with the valuesreported inTable 8Moreover Sohrabi et al [19] also reportedpH to be the most significant factor (percent contribution8490) while demonstrating Fenton and photo-Fenton pro-cess This observation can be supported by the fact thatat high pH values decomposition of H

2O2to oxygen and

formation of hydroxocomplex take place which results in lowefficiency of Fenton oxidation even at optimum conditionsof Fentonrsquos reagent [41] Thus with confidence level of 95it has been confirmed that Taguchi method with minimumnumber of experiments can be used as an alternative to CCD

for Fenton oxidation In order to confirm it optimized valuesfor the responses were computed to countercheck it with thatof CCD

53 Confirmation Test and Optimization of Operating Param-eters by Taguchi Method In Taguchirsquos method confirmationtest is important to verify the experimental results Howeverthis method has limitations for multiple response processeslike Fenton oxidation This is because unlike CCD it sug-gests individual sets of optimized parameters for individualresponses In the present case study decolorization andCOD removal efficiencies were selected as responses fordetermining the optimized set of the input variables Figure 5shows the best conditions for the Fenton oxidation Thehighest 119878119873 ratios corresponding to the COD and colorremoval suggest the best levels for each of the parameters Itcan be seen from the figure that pH shows the highest 119878119873ratio for both COD and color removal efficiencies Thus itconfirms themaximumcontribution of pH toCODand colorremoval efficiencies

Figure 5 shows the effect of operating parameters onCOD and color removal efficiency in terms of 119878119873 ratioThe highest 119878119873 ratios corresponding to the COD and colorremoval is desirable and suggests the best levels for each of theparameters In the present example Dye (119871

3) Dye Fe+2 (119871

1)

H2O2 Fe+2 (119871

3) and pH (119871

1) were optimized conditions

for COD removal efficiency while Dye (1198713) Dye Fe+2 (119871

2)

H2O2 Fe+2 (119871

3) and pH (119871

1) were the optimized set for

decolorization Optimized values corresponding to theselevels are given in Table 10

Evaluation of operating parameters by using interactionplots indicates that dye concentration of 200mgL in differentcombinations with other parameters shows maximum CODand decolorization efficiency The interaction plots wereproduced inMinitab and are provided in supplementary datain Figures A7 and A8 From the figures it can be seen thatpH at 119871

1shows maximum efficiency for all combinations of

operating parameters However dye concentration at 1198712in

combinationwithDye Fe+2 of 30 showed 80COD removalefficiency Same results were obtained when H

2O2 Fe+2 ratio

was set at 25 Similar trend was observed while studying theinteractive effects of operating parameters for determining

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

The Scientific World Journal 11

Table 9 ANOVA results

Factors Degree of freedom Sum of squares Mean Square 119865 ratio 119875 value Percent contribution ()COD ()

Dye 2 45 45 004 0961 132Dye Fe+2 2 167 167 015 0860 489H2O2 Fe

+2 2 211 211 020 0826 617pH 2 29953 29953 2123 0002 8762

Decolorization ()Dye 2 533 267 083 0482 216Dye Fe+2 2 188 94 025 0789 761H2O2 Fe

+2 2 96 48 012 0888 387pH 2 1651 826 607 0036 662

decolorization efficiency and maximum 99 decolorizationefficiency was obtained Comparison of the findings of theinteractive plots of both types of statistical techniques showedthat Taguchi method with simple graphical presentation canwell explain the interaction of operating parameters Theresults obtained were in good agreement with each otherThus Taguchi method can be used as a substitute for CCDfor assessing the experimental results

Predicted values of the responses for these optimizedvalues can be computed by using (6)This equation considersonly significant parameters Although only pH is significantparameter according to ANOVA analysis Dye Dye Fe+2and H

2O2 Fe+2 have to be optimized to maximize the COD

removal and decolorization efficiency The predicted 119878119873ratios for optimized conditions were computed and obtainedvalues were 3796 and 3994 for COD and color removalrespectively The predicted and actual values obtained as aresult of confirmation test are also given in Table 9 The pre-dicted values obtained through Taguchi method were almostclose to those obtained through CCD except H

2O2 Fe+2

ratiosThe H2O2 Fe+2 ratio is higher when compared to that

obtained with CCD the main reason for this is that withdesign expert it is possible to select the desired range forexperimental parameters With CCD H

2O2 Fe+2 ratio was

selected as the lowest one However experimental resultsobtained under optimized conditions (Taguchi method) areclose to predicted values as well as those obtained in CCDThis shows that for optimizing operating parameters forFenton oxidation Taguchimethod is suitable and economicalapproach and can be used as a substitute to central compositedesign

6 Conclusion

This study was planned to compare two optimization tech-niques such as central composite design and Taguchi orthog-onal array and Fenton oxidation with four parameters thatis [Dye]ini Dye Fe+2 H

2O2 Fe+2 and pH were selected as a

case study From this study the following points can be drawnas conclusion

(i) Taguchi method offered nine experiments for ana-lyzing the Fenton oxidation process while CCD sug-gested 30 experiments

(ii) At optimized conditions Fenton process would beable to achieve 81 and 79 COD removal efficiencyand 99 decolorization efficiency for both CCD andTaguchi method respectively

(iii) 119878119873 ratios and ANOVA under Taguchi methodshowed pH to be the most contributed factor withpercent contribution of 8762 and 662 for CODand decolorization efficiency respectively

(iv) Interactive study of operating parameters by 3Dcontour plots produced by CCD also exhibits pH andH2O2 Fe+2 the most significant factors However

quantification of contribution is not possible withCCD

Thus it can be concluded that Taguchi method is arobust statistical tool for experimental design and processoptimization Data analysis and optimization of operatingparameters are possible with fewest numbers of experimentsless computational experience and graphs obtained whichare easy to read and understand The optimized valuesobtained for both cases were in good agreement with eachother which shows the potential of Taguchi method to beused in chemical engineering applications Therefore it canbe concluded that it can be used as a substitute for centralcomposite design for Fenton oxidation process

Abbreviations

AOPs Advance oxidation processFe+2 Ferrous ironFe+3 Ferric ironH2O2 Hydrogen peroxide

HO∙ Hydroxyl radicalOFAT One factor at timeDOE Design of experimentsCCD Central composite designRSM Response surface methodologyANN Artificial neural networkANOVA Analysis of varianceSN Signal to noise ratio

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

12 The Scientific World Journal

38

36

34

32

30

Dye

100 200 300 10 30 50

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

38

36

34

32

30

Mea

n of

SN

ratio

s 38

36

34

32

30

Mea

n of

SN

ratio

s

5 15 25 20 55 90

pH

Dye Fe

H2O2 Fe

(a)

Mea

n of

SN

ratio

s

Dye

pH

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

Mea

n of

SN

ratio

s

398

396

394

392

390

1 2 3 1 2 3

1 2 3 1 2 3

Dye Fe+2

H2O2 Fe+2

(b)

Figure 5 Mean 119878119873 ratio for (a) COD removal and (b) decolorization

Table 10 Optimized values for COD removal and decolorization

Dye Dye Fe+2 H2O2 Fe+2 pH Predicted Actual

COD removal 300 10 25 3 7906 812Decolorization 300 15 25 3 9931 9904

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

The Scientific World Journal 13

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to the Faculty of Engineering Uni-versity ofMalayaUniversity ofMalayaHigh Impact ResearchGrant (HIR-MOHE-D000037-16001) from the Ministry ofHigher Education Malaysia and University of Malaya BrightSparks Unit which financially supported this work

References

[1] R Andreozzi V Caprio A Insola and R Marotta ldquoAdvancedoxidation processes (AOP) for water purification and recoveryrdquoCatalysis Today vol 53 no 1 pp 51ndash59 1999

[2] L Gomathi Devi S Girish Kumar K Mohan Reddy and CMunikrishnappa ldquoPhoto degradation of Methyl Orange an azodye byAdvanced FentonProcess using zero valentmetallic ironInfluence of various reaction parameters and its degradationmechanismrdquo Journal of Hazardous Materials vol 164 no 2-3pp 459ndash467 2009

[3] K Ntampegliotis A Riga V Karayannis V Bontozoglou andG Papapolymerou ldquoDecolorization kinetics of Procion H-exldyes from textile dyeing using Fenton-like reactionsrdquo Journal ofHazardous Materials vol 136 no 1 pp 75ndash84 2006

[4] B H Hameed and T W Lee ldquoDegradation of malachite greenin aqueous solution by Fenton processrdquo Journal of HazardousMaterials vol 164 no 2-3 pp 468ndash472 2009

[5] X Zhu and B E Logan ldquoUsing single-chamber microbial fuelcells as renewable power sources of electro-Fenton reactors fororganic pollutant treatmentrdquo Journal of Hazardous Materialsvol 252-253 pp 198ndash203 2013

[6] B H Diyarsquouddeen A R Abdul Aziz and W M A W DaudldquoOn the limitation of Fenton oxidation operational parametersa reviewrdquo International Journal of Chemical Reactor Engineeringvol 10 no 1 article R2 2012

[7] A Ellert andAGrebe ldquoProcess optimizationmade easy designof experiments with multi-bioreactor system BIOSTAT QplusrdquoNature Methods vol 8 no 4 2011

[8] P W Araujo and R G Brereton ldquoExperimental design IIOptimizationrdquo TrAC Trends in Analytical Chemistry vol 15 no2 pp 63ndash70 1996

[9] R Leardi ldquoExperimental design in chemistry a tutorialrdquoAnalytica Chimica Acta vol 652 no 1-2 pp 161ndash172 2009

[10] M B Kasiri H Aleboyeh and A Aleboyeh ldquoModelingand optimization of heterogeneous photo-fenton process withresponse surface methodology and artificial neural networksrdquoEnvironmental Science and Technology vol 42 no 21 pp 7970ndash7975 2008

[11] M AzamiM Bahram and S Nouri ldquoCentral composite designfor the optimization of removal of the azo dyeMethyl Red fromwaste water using Fenton reactionrdquo Current Chemistry Lettersvol 2 no 2 pp 57ndash68 2013

[12] D B Hasan A R A Aziz and W M A Wan Daud ldquoUsingD-optimal experimental design to optimise remazol blackB mineralisation by Fenton-like peroxidationrdquo EnvironmentalTechnology vol 33 no 10 pp 1111ndash1121 2012

[13] E C Catalkaya and F Kargi ldquoResponse surface analysisof photo-fenton oxidation of simazinerdquo Water EnvironmentResearch vol 81 no 7 pp 735ndash742 2009

[14] T J S Anand ldquoDOE based statistical approaches inmodeling oflaser processingmdashreview and suggestionrdquo International Journalof Engineering amp Technology IJET-IJENS vol 10 no 4 pp 1ndash72010

[15] L A Lu Y S Ma A Daverey and J G Lin ldquoOptimization ofphoto-Fenton process parameters on carbofuran degradationusing central composite designrdquo Journal of EnvironmentalScience and Health - Part B Pesticides Food Contaminants andAgricultural Wastes vol 47 no 6 pp 553ndash561 2012

[16] F Torrades S Saiz and J A Garcıa-Hortal ldquoUsing centralcomposite experimental design to optimize the degradation ofblack liquor by Fenton reagentrdquo Desalination vol 268 no 1ndash3pp 97ndash102 2011

[17] A Zuorro M Fidaleo and R Lavecchia ldquoResponse surfacemethodology (RSM) analysis of photodegradation of sulfonateddiazo dye Reactive Green 19 by UVH

2O2processrdquo Journal of

Environmental Management vol 127 pp 28ndash35 2013[18] T C Cheng K S Yao Y H Hsieh L L Hsieh and C Y Chang

ldquoOptimizing preparation of the TiO2thin film reactor using the

Taguchi methodrdquoMaterials and Design vol 31 no 4 pp 1749ndash1751 2010

[19] M R Sohrabi A Kavaran S Shariati and S Shariati ldquoRemovalof Carmoisine edible dye by Fenton and photo Fenton processesusing Taguchi orthogonal array designrdquo Arabian Journal ofChemistry 2014

[20] K C Namkung A E Burgess D H Bremner and H StainesldquoAdvanced Fenton processing of aqueous phenol solutions acontinuous system study including sonication effectsrdquoUltrason-ics Sonochemistry vol 15 no 3 pp 171ndash176 2008

[21] M A Bezerra R E Santelli E P Oliveira L S Villar and L AEscaleira ldquoResponse surface methodology (RSM) as a tool foroptimization in analytical chemistryrdquo Talanta vol 76 no 5 pp965ndash977 2008

[22] L YeM Ying L Xu C Guo L Li andDWang ldquoOptimizationof inductive angle sensor using response surface methodologyand finite element methodrdquoMeasurement vol 48 pp 252ndash2622014

[23] T Olmez ldquoThe optimization of Cr(VI) reduction and removalby electrocoagulation using response surface methodologyrdquoJournal of Hazardous Materials vol 162 no 2-3 pp 1371ndash13782009

[24] S Baroutian M K Aroua A A A Raman and N M NSulaiman ldquoA packed bed membrane reactor for production ofbiodiesel using activated carbon supported catalystrdquoBioresourceTechnology vol 102 no 2 pp 1095ndash1102 2011

[25] D Montgomery Design and Analysis of Experiments JohnWiley amp Sons New York NY USA 2001

[26] A El-Ghenymy S Garcia-Segura R M Rodrıguez E BrillasM S El Begrani and B A Abdelouahid ldquoOptimization ofthe electro-Fenton and solar photoelectro-Fenton treatments ofsulfanilic acid solutions using a pre-pilot flow plant by responsesurface methodologyrdquo Journal of Hazardous Materials vol 221-222 pp 288ndash297 2012

[27] N Ali V F Neto S Mei et al ldquoOptimisation of the new time-modulated CVD process using the Taguchi methodrdquoThin SolidFilms vol 469-470 pp 154ndash160 2004

[28] S Maghsoodloo G Ozdemir V Jordan and C HuangldquoStrengths and limitations of taguchirsquos contributions to quality

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

14 The Scientific World Journal

manufacturing and process engineeringrdquo Journal of Manufac-turing Systems vol 23 no 2 pp 73ndash126 2004

[29] G Barman A Kumar and P Khare ldquoRemoval of congo red bycarbonized low-cost adsorbents process parameter optimiza-tion using a Taguchi experimental designrdquo Journal of Chemicaland Engineering Data vol 56 no 11 pp 4102ndash4108 2011

[30] S K Gauri and S Chakraborty ldquoMulti-response optimisationof WEDM process using principal component analysisrdquo TheInternational Journal of Advanced Manufacturing Technologyvol 41 no 7-8 pp 741ndash748 2009

[31] P J Ross Taguchi Techniques for Quality Engineering McGraw-Hill New York NY USA 1998

[32] M Kaladhar K V Subbaiah C Srinivasa Rao and K NarayanaRao ldquoApplication of Taguchi approach and utility concept insolving the multi-objective problem when turning AISI 202austenitic stainless steelrdquo Journal of Engineering Science andTechnology Review vol 4 no 1 pp 55ndash61 2011

[33] C L Hsueh Y H Huang C C Wang and C Y ChenldquoDegradation of azo dyes using low iron concentration ofFenton and Fenton-like systemrdquo Chemosphere vol 58 no 10pp 1409ndash1414 2005

[34] S Wang ldquoA Comparative study of Fenton and Fenton-likereaction kinetics in decolourisation of wastewaterrdquo Dyes andPigments vol 76 no 3 pp 714ndash720 2008

[35] M Neamtu A Yediler I Siminiceanu and A Kettrup ldquoOxi-dation of commercial reactive azo dye aqueous solutions bythe photo-Fenton and Fenton-like processesrdquo Journal of Pho-tochemistry and Photobiology A Chemistry vol 161 no 1 pp87ndash93 2003

[36] M Y Can Y Kaya and O F Algur ldquoResponse surfaceoptimization of the removal of nickel from aqueous solution bycone biomass of Pinus sylvestrisrdquo Bioresource Technology vol97 no 14 pp 1761ndash1765 2006

[37] B K Korbahti ldquoResponse surface optimization of electrochem-ical treatment of textile dye wastewaterrdquo Journal of HazardousMaterials vol 145 no 1-2 pp 227ndash286 2007

[38] B Bianco I de Michelis and F Veglio ldquoFenton treatmentof complex industrial wastewater optimization of processconditions by surface response methodrdquo Journal of HazardousMaterials vol 186 no 2-3 pp 1733ndash1738 2011

[39] C T Benatti C R G Tavares and T A Guedes ldquoOptimizationof Fentonrsquos oxidation of chemical laboratory wastewaters usingthe response surface methodologyrdquo Journal of EnvironmentalManagement vol 80 no 1 pp 66ndash74 2006

[40] M Ahmadi F Vahabzadeh B Bonakdarpour E Mofarrah andM Mehranian ldquoApplication of the central composite designand response surface methodology to the advanced treatmentof olive oil processing wastewater using Fentonrsquos peroxidationrdquoJournal of Hazardous Materials vol 123 no 1ndash3 pp 187ndash1952005

[41] YW Kang andKHwang ldquoEffects of reaction conditions on theoxidation efficiency in the Fenton processrdquoWater Research vol34 no 10 pp 2786ndash2790 2000

[42] S Meric D Kaptan and T Olmez ldquoColor and COD removalfrom wastewater containing Reactive Black 5 using Fentonrsquosoxidation processrdquo Chemosphere vol 54 no 3 pp 435ndash4412004

[43] M E Argun and M Karatas ldquoApplication of Fenton processfor decolorization of reactive black 5 from synthetic wastewa-ter kinetics and thermodynamicsrdquo Environmental Progress ampSustainable Energy vol 30 no 4 pp 540ndash548 2011

[44] A Chowdhury R Chakraborty D Mitra and D BiswasldquoOptimization of the production parameters of octyl ester biol-ubricant using Taguchirsquos design method and physico-chemicalcharacterization of the productrdquo Industrial Crops and Productsvol 52 pp 783ndash789 2014

[45] O Gokkus Y S Yildiz and B Yavuz ldquoOptimization of chemicalcoagulation of real textile wastewater using Taguchi experimen-tal design methodrdquo Desalination and Water Treatment vol 49no 1ndash3 pp 263ndash271 2012

[46] O Gokkus and Y S Yıldız ldquoInvestigation of the effect of processparameters on the coagulationflocculation treatment of textilewastewater using the taguchi experimental methodrdquo FreseniusEnvironmental Bulletin vol 23 no 2 pp 1ndash8 2014

[47] L Hsieh H Kang H Shyu and C Chang ldquoOptimal degra-dation of dye wastewater by ultrasoundFenton method in thepresence of nanoscale ironrdquoWater Science and Technology vol60 no 5 pp 1295ndash1301 2009

International Journal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

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Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of