EVALUATION OF GRINDING PROCESS PARAMETERS … · cylindrical grinding machine using Box-Behnken Design (BBD ... introduced and high wear rates of the cutting tools are experienced

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 10, October 2017, pp. 190–206, Article ID: IJMET_08_10_024

Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

EVALUATION OF GRINDING PROCESS

PARAMETERS OF AL/ SIC COMPOSITE USING

DESIRABILITY APPROACH

C. Thiagarajan, S. Ranganathan, V.Jayakumar, A. Muniappan and Anoop Johny

Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha

University, Chennai, Tamilnadu, India.

ABSTRACT

This paper aims at analyzing multiple grinding characteristics of Al/SiC

composites produced by stir casting. Desirability function-based approach is

employed wherein the process parameters like wheel velocity, work piece velocity,

feed rate and depth of cut were varied to obtain optimum tangential grinding force,

surface roughness and grinding temperature. Experiments were conducted on a

cylindrical grinding machine using Box-Behnken Design (BBD). Experiments were

carried out using Al2O3 grinding wheel of diameter 300 mm. Empirical models were

developed for the grinding process parameters of Al/SiC composites for predicting the

optimum tangential grinding force, surface roughness and grinding temperature. The

results showed that high wheel velocity, medium work piece velocity, low feed rate

and low depth of cut are necessary to minimize the tangential grinding force, surface

roughness and grinding temperature for grinding of Al/SiC composites.

Keywords: Al/SiC Composites; Response Surface Methodology, Grinding

Characteristics, Stir Casting.

Cite this Article: C. Thiagarajan, S. Ranganathan, V. Jayakumar, A. Muniappan and

Anoop Johny, Evaluation of Grinding Process Parameters of Al/ Sic Composite using

Desirability Approach, International Journal of Mechanical Engineering and

Technology 8(10), 2017, pp. 190–206.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10

1. INTRODUCTION

Metal matrix composites are nonhomogeneous, anisotropic and reinforced by very abrasive

components and they are difficult to machine. Significant damage to the workpiece may be

introduced and high wear rates of the cutting tools are experienced during machining. Light

weight components in industrial sectors have a choice of Aluminium alloys whose superior

mechanical and physical properties coupled with light weight make them suitable for new

product development applications. Aluminium alloys reinforced with silicon carbide particles

are potentially useful structural materials, with high strength, high modulus values, and are

used in various industrial applications. These applications warrant machining of the

Evaluation of Grinding Process Parameters of Al/ Sic Composite using Desirability Approach


composites. Despite all these large applications, the Al/SiC composites are challenging to

machine to obtain a good surface finish. The main concern in machining of Al/SiC

composites is the extremely high tool wear, due to the abrasive action of the SiC particles and

needs to be addressed for the successful application of these composites. Sun et al reported

that, the grinding is an important finish-machining process that is widely used in the

manufacture of components requiring fine tolerances and smooth finish. Since the problems

associated with the machining of Al/SiC composites are large, they cannot be applied with

ease [1]. Varol and Canakci studied the effect of weight percentage and particle size of B4C

reinforcement on physical and mechanical properties of Al 2024- B4C composites [2]. The

grinding problems can be minimized, if not eliminated by the careful selection of appropriate

grinding parameters and other important conditions, like the percentage of SiC volume

fraction to improve the surface finish. Methods to produce the Al/SiC composites and studies

on their machining characteristics have been reported [3-5]. Quan and Ye stated that the

presence of SiC in the metal matrix influence to increase the hardness, tensile strength and

heat resistance of the composites. However during the machining of Al/SiC composites using

conventional methods, the presence of hard SiC particles causes problems like cracking and

splintering [6]. Canakci et al predicted the effect of volume fraction, compact pressure and

milling time on properties of Al-Al2O3 MMCs using neural networks [7]. Canakci et al

developed a stir casting process to produce aluminum alloy composites containing two

different sizes and volume fraction of B4C particles upto 10 % volume [8]. Slowik and

Slowik presented the multi objective optimization of a surface grinding process using

evolutionary algorithm [9]. Saravanan et al reported the genetic algorithm based optimization

procedure to optimize the grinding conditions [10]. Zhong et al studied the grinding of

Al/Al2O3 MMCs using grinding wheels having SiC in a vitrified matrix and diamond in a

resin-bonded matrix and discussed the surface roughness, grinding force, type and size of the

abrasives, grinding conditions, and the consequential sub-surface integrity [11]. Jae-Seob

Kwak presented the application of Taguchi and response surface methodologies for the

geometric error in surface grinding process and evaluated the optimum grinding conditions

[12]. Shaji and Radhakrishnan investigated the analysis of process parameters in surface

grinding with graphite lubricant based on the Taguchi method [13]. Aykut Canakci et al

determined the effect of process parameters on particles size in mechanical milling using the

Taguchi method. In their study the orthogonal array experiment was conducted to

economically obtain the response measurement and determined the significant parameters and

set the optimal level for each parameter [14]. Desirability functions have been used

extensively to simultaneously optimize several responses. Since the original formulation of

these functions contains non-differentiable points, only search methods can be used to

optimize the overall desirability response. Furthermore, all responses are treated as equally

important [15]. Teti reported that conventional machining process like turning, drilling and

milling of composite materials require proper selection of tools and process parameters for

less tool wear and damage [16]. The hard SiC particle of Al/SiC composites which

intermittently come into contact with hard surface, act as small cutting edges on the tool,

which in due course, is worn out by abrasion and resulting in the formation of poor surface

finish during grinding . This makes the grinding of a Al based MMCs a difficult and

unpredictable process. The difficulties associated with the grinding of MMCs must be

minimized if these materials are to be used more extensively [17]. Unlike the investigations

into the grinding of traditional metallic materials, not much research has been carried out on

the grinding of MMCs. Though many researchers [18-20] had carried out experimental works

under different grinding conditions in a surface grinding machine, the grinding of Al/SiC

composites using a cylindrical machine under various grinding conditions is yet to be

investigated. This made researchers to undergo a detailed study and optimization of process



parameters on grinding of Al/SiC composites. In continuation of this trend, the cylindrical

grinding experiments were conducted using cylindrical grinding machine for the grinding of

Al/SiC composites and the performance is reported in this paper. Box-Behnken experimental

design is considered for this investigation because this method requires three levels for each

factors and the total number of experimental run is less than that of central composite design

[21] Empirical relations were developed to predict the tangential grinding force (Ft), surface

roughness (Ra), and grinding temperature (Tg) using response surface methodology. Analysis

of variance (ANOVA) is used for checking the significance of the developed model. The

results of desirability-function approach showed that the high wheel velocity, medium work

piece velocity, low feed rate and low depth of cut are necessary to minimize the tangential

grinding force, surface roughness and grinding temperature for grinding of Al/SiC

composites.

2. EXPERIMENTAL PROCEDURE

2.1 Fabrication of Workpiece

Al/SiC composite specimens were fabricated by the addition of SiC reinforcement (particle

size 13 µm) to the LM25 aluminium alloy matrix with the dimensions of φ30 × 200 mm and

the morphology of the SiC particle ( Supplier-Krish Met Tech Pvt. Ltd, Chennai) is shown in

the Figure 1. The chemical composition and the properties of the LM25 aluminium alloy

(Supplier - Sargam Metal Pvt. Ltd, Chennai) are given in Table 1 and Table 2 respectively.

Figure 1 Morphology of the as received SiC particles

Table 1 Chemical composition of the LM25 aluminum alloy

Elements Cu Si Mg Mn Fe Ni Ti Zn Pb Sn

Compositions

(%) 0.2

6.5-

7.5

0.2-

0.6 0.3 0.5 0.1 0.2 0.1 0.1 0.05

Table 2 Properties of the LM25 aluminium alloy and SiC particles

Properties Density

(g/cm3)

Coefficient of

thermal

expansion

(× 10-6

/°C)

Thermal

conductivity

(W/mK)

Modulus of

elasticity

(GPa)

Poisson’s

ratio

LM25 Al

alloy 2.68 22 151 71 0.33

SiC 3.2 4.7 200 415 0.18

This composite can be synthesized more easily by the stir casting process since stir casting

is a relatively inexpensive processing method, and offers a wide selection of materials and

processing conditions and involves the addition of SiC particles into the semi-solid aluminium



metal by means of agitation (stirring) [22]. The Al/SiC specimens in the ‘as-cast’ condition

and the stir casting set-up used to fabricate them, are shown in Figures 2 and 3 respectively.

Figure 2 LM25Al/SiC specimens in the ‘as-cast’ condition

Figure 3 Stir casting set-up used to fabricate Al/SiC specimens

The SEM micro structure of the LM25Al/SiC in Figure 4 shows the uniform distribution

of the SiC particles in the aluminium matrix.

Figure 4 Uniform distribution of the SiC particles in the aluminium matrix

Further to the SEM analysis, the samples were subjected to the EDX analysis, in order to

ascertain the presence of the SiC particles in the metal matrix. SEM and EDX clearly reveal

the presence and distribution of the SiC particles in the aluminium matrix is shown in Figure

5.

Field of view for EDX analysis Compound %

C Al Si

Base(2520)_pt1 12.72 1.48 85.79

Figure 5 SEM surface and EDX analysis



2.2 Selection of Grinding Wheel

The grinding wheel plays a key role in the grinding process that could produce high

machining accuracy and good surface finish of the work piece. Among the types of grinding

wheels employed in the experimental tests, the wheels manufactured with conventional

abrasives have given better performances than super abrasive wheels, in terms of low

clogging, low grinding forces and better surface finish. The lowest tendency to clogging

occurs with the aluminium oxide wheel [23]. As far as machining of SiC is concerned, Al2O3

is a better choice as wheel material over SiC wheel. The specification of the grinding wheel

used in the present study is as follows

Grinding wheel specification- AA 60K5V8

Type of abrasive AA (Alumnium Ooxide), Grain size 60 (Medium), Grade K (Soft),

Structure 5 (Dense), Type of bond V8 (Vitrified)

2.3 Experimental Details

The experiments were carried out as per Box-Behnken experimental design with three levels

defined for each of the four process parameters. Grinding performance of Al/SiC composites

was studied by conducting various machinability tests using Al2O3 grinding wheel. The

experiments were conducted on horizontal spindle cylindrical grinding machine (Type G13P,

HMT make) with the available wheel velocity ranges from 1500 rpm to 2800 rpm; feed rate

of 0.06 m/min to 0.17 m/min. This decides the grinding conditions and their levels and the

setup is shown in Figure 6.

Figure 6 Experimental set-up

A device called Variable Frequency Drive (VFD) was used to measure the power of the

grinding wheel motor. The value of tangential grinding force can be calculated by measuring

the power of the grinding wheel motor. The surface finish is a direct process result, and was

measured by a stylus based surface roughness tester. The temperature generated during

grinding is a direct sequence of the energy input to the process, and was measured by a non-

contact infrared thermo meter. The schematic diagram of the experimental set-up is shown in

Figure 7.

Figure 7 Schematic diagram of the experimental set-up



Based on the Box-Behnken experimental design, the experiments were conducted by

varying the four parameters, namely, the wheel velocity (Vw), workpiece velocity (Vc), feed

(f) and depth of cut (ap) at three levels [21]. The operating grinding conditions designed by

Box-Behnken method were set using the variable frequency drive and are shown in Table 3.

Table 3 Grinding conditions and their levels

Parameters

Levels

1

Low

2

Medium

3

High

Wheel velocity, Vw (m/min) 1414 2026.5 2639

Workpiece velocity, Vc (m/min) 6.11 16.41 26.72

Feed rate- Work table traverse, f (m/min) 0.06 0.12 0.17

Depth of cut, ap (µm) 10 20 30

2.4 Measurement of Grinding Responses

A device called VFD (ACS 350-03E-12A5-4, ABB make) was used to measure the power of

the grinding wheel motor to calculate the tangential grinding force (Ft). It is a device used to

control the rotational speed of an alternating current (AC) electric motor, by controlling the

frequency of the electrical power supplied to the motor. The VFD was attached to the

grinding wheel motor for changing the wheel speed.

Measuring the power P by the VFD and knowing the wheel velocity Vw, the tangential

grinding force (Ft) can be calculated [25] as

w

tV

PF

94535 =

Where Ft = Tangential grinding force in N, P = Power in KW and Vw = Wheel velocity in

m/min

The surface roughness (Ra) of the ground specimens was measured in the direction

perpendicular to the grinding direction, using a stylus based surface roughness tester

(Surfcorder-SE1200, Kosaka) is shown in Figure 8.

Figure 8 Surface roughness tester

The cut-off was 0.8 mm and the traverse length was 4 mm during the measurement of

surface roughness (Ra ). On each ground surface three values were measured to calculate the

average Ra. A non-contact infrared thermometer (MT-9, METRAVI make) was used to

measure the grinding zone temperature is shown in Figure 9. It was ascertained from the

experimental results that the spark temperature can be considered to be a good representative

of the grinding zone temperature [25-26]. The results of grinding experiment of Al/SiC

composites are shown in the Table 4.



Figure 9 Non-contact infrared thermometer

2.5 Response surface method

Response surface method is used to predict the tangential grinding force, surface roughness

and grinding temperature. Response surface methodology (RSM) is an advanced tool,

commonly applied involving three factorial designs giving number of input (independent)

factors and their corresponding relationship between one or more measured dependent

responses [29-30].

Table 4 Experimental results of the grinding of Al/SiC composites

No. Vw m/min Vc m/min F m/min ap µm Ft N Ra µm Tg 0C

1 1414 6.11 0.12 0.02 26 0.521 747

2 2639 6.11 0.12 0.02 24 0.124 802

3 1414 26.72 0.12 0.02 27 0.647 754

4 2639 26.72 0.12 0.02 17 0.128 795

5 2026.5 16.41 0.06 0.01 18 0.321 782

6 2026.5 16.41 0.17 0.01 25 0.397 783

7 2026.5 16.41 0.06 0.03 26 0.398 784

8 2026.5 16.41 0.17 0.03 30 0.412 780

9 1414 16.41 0.12 0.01 30 0.548 745

10 2639 16.41 0.12 0.01 19 0.122 800

11 1414 16.41 0.12 0.03 35 0.684 756

12 2639 16.41 0.12 0.03 20 0.148 804

13 2026.5 6.11 0.06 0.02 30 0.368 784

14 2026.5 26.72 0.06 0.02 22 0.342 789

15 2026.5 6.11 0.17 0.02 27 0.324 786

16 2026.5 26.72 0.17 0.02 25 0.312 785

17 1414 16.41 0.06 0.02 24 0.547 751

18 2639 16.41 0.06 0.02 22 0.101 800

19 1414 16.41 0.17 0.02 30 0.547 756

20 2639 16.41 0.17 0.02 24 0.147 802

21 2026.5 6.11 0.12 0.01 30 0.329 798

22 2026.5 26.72 0.12 0.01 20 0.348 789

23 2026.5 6.11 0.12 0.03 21 0.32 795

24 2026.5 26.72 0.12 0.03 29 0.398 799

25 2026.5 16.41 0.12 0.02 26 0.348 795

26 2026.5 16.41 0.12 0.02 28 0.308 796



27 2026..5 16.41 0.12 0.02 29 0.348 797

28 2026.5 16.41 0.12 0.02 26 0.391 790

29 2026.5 16.41 0.12 0.02 27 0.348 792

A simpler and more efficient statistical model using RSM was designed in Design-Expert

8 evaluation software package. The response surface method used to predict tangential

grinding force, surface roughness and grinding temperature of grinding of Al/SiC composites.

RSM creates polynomial models for the available data set in the following equation.

Y = β0 +i

n

i

i x∑=1

β +

i

n

i

i x2

1

∑=

β

+ ji

n

i

n

j

ij xx∑∑= =1 1

β + ε (1)

Where β0, β i and β ij are grinding process parameters at different grinding level and n is

the number of model parameters. In creating RSM models 29 experimental data

measurements were obtained and shown in Table 4.

The measured responses tangential grinding force, surface roughness and grinding

temperature can be expressed as a function of grinding process parameters such as wheel

velocity (Vw), work piece velocity (Vc), feed rate (f) and depth of cut (ap). The generalized

polynomial response-surface model used to estimate the parametric effects is as follows

Y = β0 + ( )wV1β + ( )cV2β

+ ( )f3β + ( )pa4β + ( )( )cw VV5β + ( )( )fVw6β + ( )( )

pw aV7β +

( )( )fVc8β + ( )( )pc aV9β + ( )( )

paf10β + ε (2)

Where Y is the response, Vw, Vc, f and ap are variables representing different grinding

parameters, βs are regression coefficients and ε represents error associated with the model.

The model chosen in this paper includes the effects of four main factors and its interaction

(Ft) =+37.8044 -1.0571 X 10-3

Vw – 0.3767 Vc+ 28.7878f–558.4788 ap – 3.1686 X

10-4

Vw Vc + 43.6681 Vw ap R2=0.7402 (3)

Similarly the relationship between the surface roughness and grinding temperature are

expressed as follows:

Surface Roughness (Ra) = +0.751- 2.40753 X 10-4

Vw +7.74801 X 10-3

Vc -0.13558 f

+12.44826 - 4.83221 X 10-6

VwVc + 3.41373 X 10-4

Vw f - 4.48980 X 10-3

Vw ap +0.14313Vc

ap R2 = 0.9661 (4)

Grinding Temperature (Tg) =+473.08329 +0.21853 Vw+1.11127Vc +605.91542f+

314.33258 ap -5.54516 X 10-4

Vw Vc - 0.022263 Vwf -0.28571 Vw ap -3.97612X 10-5

Vw2 - 20416.66667 ap

2 R

2 = 0.9616 (5)

The adequacy of the model is further analyzed by using R-Sq (R2) values. The values of

R-Sq represent the regression confidence. The larger value of R-Sq is always desirable [31-

32]. In the present case, the R-Sq values are 0.7402, 0.9661 and 0.9616which show a high

correlation between the experimental values and predicted values.

In this study, S/N ratios were calculated using a ‘‘smaller is better’’ approach and its S/N

ratio is calculated as follows;

S/N ratio ]

n

1 [ log

1

2

∑=

10− =n

i

iyη (6)

The average S/N ratio values, calculated for each factor at a given level, allow the

establishment of the best levels. It was found that the best parameters for tangential force and

their levels are A3B1C2D2, for surface roughness A3B3C1D3 and for grinding temperature

A1B1C2D1 are shown in Figures 10, 11 and 12 for the main effect of grinding of Al/SiC

composites.



Figure 10 The main effect plot for Tangential force of grinding of Al/SiC composites

Figure 11 The main effect plot for surface roughness of grinding of Al/SiC composites

Figure 12 The main effect plot for grinding temperature of grinding of Al/SiC composites

3. RESULTS AND DISCUSSION

Aluminium alloy with SiC composite materials are finding many applications like aerospace,

automotive, marine, building, packaging industries and many engineering components.

Grinding of these components cannot be avoided and the experiments are conducted for

analyzing the influence of grinding parameters to give the best combination of the machining

conditions. Grinding wheel velocity, work piece velocity, feed rate and depth of cut are the

major grinding process parameters that are considered in these experiments. Tangential

grinding force, surface roughness and grinding temperature were the minimization quantities

and should be optimized in terms of the process parameters. In this work, the multiple

performance optimization of grinding process parameters was carried out using response-

321

-57.6

-57.7

-57.8

-57.9

-58.0

-58.1

-58.2

321 321 321

Wheel Velocity

Mean

Work piece Velocity Feed rate Depth of Cut

Main Effects Plot for Grinding TemperatureData Means



surface methodology based on desirability- function approach. The developed model is

evaluated and validated by using analysis of variance (ANOVA), Tables 5 shows the results

of tangential grinding force (Ft), surface roughness (Ra) and grinding temperature (Tg). The

optimization method was carried out using DESIGN-EXPERTS software. Table 6 shows the

best results obtained by the desirability approach. Based on the goal set, optimization is

carried out for combination of goals. The goals are applied to the factors and responses for

optimization of the grinding process parameters. The goals used for tangential grinding force,

surface roughness and grinding temperature are “minimize” and the goals used for the factors

are “within range”. The histogram of the desirability for the best solution is shown in Figure

13 and represents the desirability for each factor and response individually.

The measurement of the tangential grinding force (Ft) is highly essential to analyze the

cylindrical grinding parameters more effectively. The effect of wheel velocity, work piece

velocity, feed and depth of cut on Ft is shown in Figure 14. It is observed from the results

shown in Figure 14 that the tangential grinding force (Ft) decreases with an increase in the

wheel velocity (Vw) and workpiece velocity (Vc). The wheel velocity is increased from 1414

m/min to

Table 5 ANOVA for Tangential Grinding Force (Ft), Surface Roughness (Ra) and Grinding

Temperature (Tg)

Source Sum of Squares

(SS) df

Mean Squares

(MS)

F

Value

ANOVA for Tangential Grinding Force (Ft)

Model 360.50 6 60.08 8.67

A- Wheel Velocity 176.33 1 176.33 25.43

B- Workpiece Velocity 27.00 1 27.00 3.89

C- Feed rate 30.08 1 30.08 4.34

D- Depth of cut 30.08 1 30.08 4.34

AB 16.00 1 16.00 2.31

BD 81.00 1 81.00 11.68

Residual 152.53 22 6.93

Lack of Fit 145.73 18 8.10 4.76

Error 6.80 4 1.70

Cor Total 513.03 28

Model 0.64 10 0.064 51.28

ANOVA for Surface Roughness (Ra)

A- Wheel Velocity 0.62 1 0.62 496.93

B- Workpiece Velocity 2.977E-003 1 2.977E-03 2.39

C- Feed rate 3.203E-004 1 3.203E-004 0.26

D- Depth of cut 7.252E-003 1 7.252E-003 5.83

AB 3.721E-003 1 3.721E-003 2.99

AC 5.290E-004 1 5.290E-004 0.43

AD 3.025E-003 1 3.025E-003 2.43

BD 9.610E-004 1 9.610E-004 0.77

Error 3.447E-003 4 8.618E-004 0.00344

Lack of Fit 0.019 14 1.354E-003 1.57

Total 0.66 28

Model 8923.58 14 637.40 25.04



ANOVA for Grinding Temperature (Tg)

A- Wheel Velocity 7203.00 1 7203.00 282.93

B- Workpiece Velocity 0.083 1 0.083 0.003273

C- Feed rate 0.33 1 0.33 0.013

D- Depth of cut 36.75 1 36.75 1.44

AB 49.00 1 49.00 1.92

AC 2.25 1 2.25 0.088

AD 12.25 1 12.25 0.48

A2 1443.29 1 1443.29 56.69

D2 27.04 1 27.04 1.06

Error 34.00 4 8.50

Lack of Fit 322.42 10 32.24 3.79

Total 9280.00 28

2639 m/min and the workpiece velocity is increased from 6.11 m/min to 26.72 m/min.

The increase in the wheel velocity and workpiece velocity leads to the thermal softening of

the aluminium matrix, which in turn, reduces the tangential grinding force.

This behavior is as similar to the literature report by Zhong [33] on grinding of

aluminium-based metal matrix composites reinforced with Al2O3 or SiC particles. As the

grinding wheel velocity increases, the heat generated in the deformation zone increases and

softens the aluminium matrix, thereby reducing the force required to remove the material.

The increase in the wheel velocity also reduces the maximum chip thickness, which

results in a requirement of lower grinding force.

Table 6 Comparison between experimental and predicted values

No Vw Vc F ap Ft (N) Ra (µm) Tg (ºC)

Ex Pre Ex Pre Ex Pre

1 2639 2077 0.06 10 15.6 15.5 0.18 0.18 767 765

2 2650 2077 0.06 10 15.4 15.5 0.18 0.18 768 769

3 2625 2077 0.06 10 15.4 15.2 0.18 0.18 768 766

Figure 13 Histogram of the greatest solution



Figure 14 Surface plot of the grinding force

These results comply with the earlier report on selection of optimum conditions for

maximum material removal rate with surface finish in SiC grinding presented by Anne Venu

Gopal and P.Venkateswara Rao [34].

Surface finish has been a key issue for the reliable prediction of the grinding performance,

and surface roughness is one of the most important parameters in assessing the quality of a

ground component. The surface roughness (Ra) of the ground specimens was measured by

conducting experiments. The effect of the cylindrical grinding parameters on Ra is shown in

Figure 15. It is observed from the results that the values of the surface roughness (Ra)

decrease with an increase in the wheel velocity (Vw) and workpiece velocity (Vc). The wheel

velocity is increased from 1414 m/min to 2639 m/min and the workpiece velocity is increased

from 6.11 m/min to 26.72 m/min. This is mainly due to the increase in the relative velocity

between the wheel and the work piece, to result in reduced contact time between them. This

situation reduces the chip thickness and a subsequent decrease in the Ra values. A similar

trend was also observed by Jae-Seob Kwak et al [35] during external cylindrical grinding of

hardened SCM440 steel.

It is observed from the results shown in Figure 15 that the values of the surface roughness

(Ra) increase with an increase in the combination of feed rate (f) and depth of cut (ap). In the

set of experiments conducted, the feed rate is increased from 0.06 m/min to 0.17 m/min and

the depth of cut is increased from 10 µm to 30 µm. The increase in the combined effect of

feed rate and depth of cut increases the wheel-work contact area, leading to an increase in grit

penetration and the subsequent maximum chip thickness, which invariably increases the

surface roughness (Ra) values.

Figure 15 Surface plot of the surface roughness

Design-Expert® Software

Grindind ForceDesign Points35

17

X1 = A: Wheel velocityX2 = B: Workpiece velocity

Actual FactorsC: Feed rate = 0.12D: Depth of cut = 0.02

1414.00 1720.25 2026.50 2332.75 2639.00

6.11

11.26

16.41

21.57

26.72Grindind Force

A: Wheel v elocity

B: W

ork

pie

ce v

elo

city

20.0249

21.9693

23.9138

25.8582

27.8027 55555

Design-Expert® Software

Grindind ForceDesign Points35

17

X1 = A: Wheel velocityX2 = B: Workpiece velocity

Actual FactorsC: Feed rate = 0.12D: Depth of cut = 0.02

1414.00 1720.25 2026.50 2332.75 2639.00

6.11

11.26

16.41

21.57

26.72Grindind Force

A: Wheel v elocity

B: W

ork

pie

ce v

elo

city

20.0249

21.9693

23.9138

25.8582

27.8027 55555



Figure 16 shows the SEM micrograph of the rough ground surface having a Ra of 0.893

µm obtained at low wheel and workpiece velocities, high feed and depth of cut (wheel

velocity 1414 m/min, workpiece velocity 6.11 m/min, feed rate 0.17 m/min and depth of cut

30 µm).

Figure 16 The SEM micrograph of rough ground surface

Figure 17 The SEM micrograph of rough ground surface

Figure 18 The SEM micrograph of fine ground surface

The banding structure (grinding wheel marks) on the work piece surface and the poor

surface finish are the effects of the grinding wheel, due to the high feed rate and depth of cut.

As a result of the higher feed rate and depth of cut, the Al2O3 grains of the wheel are

embedded on the surface of the work piece and then disintegrated.

Figure 17 shows the rough ground surface of the specimen. This surface, obtained at low

wheel and work piece velocities, high feed rate and depth of cut ( wheel velocity 1414 m/min,

work piece velocity 6.11 m/min, feed rate 0.17 m/min and depth of cut 30 µm) shows the

micro cracks and the fragmentation of the Al-Si eutectic (white globular) particles. The

development of micro cracks results from the thermal residual stress due the mismatch in the

coefficient of thermal expansion of the Al matrix and SiC particles. The fragmentation of the

Al-Si eutectic particles is due to the high feed rate and depth of cut (feed rate 0.17 m/min,

depth of cut 30 µm).

Figure 18 shows the SEM micrograph of the fine ground surface having a surface

roughness of 0.171 µm. The fine grinding marks shown on the SiC particles ensured that both

the SiC particles and the aluminium matrix were removed by cylindrical grinding at high



wheel and workpiece velocities (Vw 2639 m/min, Vc 26.72 m/min), low feed and depth of cut

( feed rate 0.06 m/min, depth of cut 10 µm). At high wheel velocity, the aluminium matrix

experienced plastic deformation, and the SiC particles were covered by the aluminium matrix.

There were no cracks and defects found on the fine ground surfaces in SEM.

Grinding temperature is one of the most important parameters affecting the quality of a

ground surface. In order to ascertain the correct grinding conditions, it is necessary to know

the effect of each of the grinding parameters and their influences on the grinding temperature.

The effect of the wheel velocity, work piece velocity, feed and depth of cut on Tg is shown in

Figure 19. Grinding temperature (Tg) increases with an increase in the wheel velocity, work

piece velocity, feed and depth of cut. The minimum value of grinding temperature is 740°C

obtained at the set of lower level grinding parameters (Vw 1414 m/min, Vc 6.11 m/min, f 0.06

m/min and ap 10 µm). The maximum value of grinding temperature is 856°C obtained at the

set of higher level grinding parameters (Vw 2639 m/min, Vc 26.72 m/min, f 0.17 m/min and ap

30 µm).

Figure 19 Surface plot of the grinding temperature

The higher values of the grinding parameters (Vw, Vc, f and ap) result in higher grinding

temperatures due to the increase of the energy required to grind a unit volume of the material.

Figure 20 Estimated surface plot of desirability

Figure 20 shows the estimated surface plot of the desirability function as 0.931. Finally,

the confirmation tests were conducted in the series of input parameters; wheel velocity 2639

m/min, work piece velocity 20.77, feed rate 0.06 m/min and depth of cut 10 µm. Table 6 gives

the details of the conformation experiments. The conformation experiments were repeated

three times and the average values have been used. The experimental values are very close

and lie within +/- 2% of the predicted values. Hence the developed models are suitable for



predicting the tangential grinding force, surface roughness and grinding temperature in

grinding of Al/SiC composites.

4. CONCLUSIONS

In this study, the optimal grinding process parameters were determined for the multi

performance characteristics such as grinding force, surface roughness and grinding

temperature by using response surface methodology and desirability based optimization.

Based on the results, the following conclusions are attained.

• The grinding process parameters in grinding of Al/SiC composites were modeled

using Response-surface methodology. The results indicate that the models are

effective in predicting the responses in grinding of Al/SiC composites.

• Based on the desirability approach, the multiple response optimization was carried out

to get optimal solution

• The optimization results showed that the values of the surface roughness (Ra)

decreases with an increase in the wheel velocity (Vw) and workpiece velocity (Vc), the

tangential grinding force (Ft) decreases with an increase in the wheel velocity (Vw) and

workpiece velocity (Vc) and the higher values of the grinding parameters such as

wheel velocity (Vw), workpiece velocity (Vc), feed rate and depth of cut result in

higher grinding temperature

• The results indicate that, the wheel velocity (Vw), workpiece velocity (Vc), and feed

rate are the main parameters which influence the grinding force, surface roughness and

grinding temperature in grinding of Al/SiC composites.

• This method is suitable and efficient to predict the effects of different significant

combination of process parameters on the grinding of Al/SiC composites within the

levels studied

NOMENCLATURE

Vw : Wheel Velocity in m/min

Vc : Workpiece Velocity in m/min

f : Feed rate in m/min

ap : Depth of cut in µm

Ft : Tangential grinding force in Newton

Ra : Surface roughness in µm

Tg : Grinding Temperature in Celsius temperature scale

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