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ISI KANDUNGAN M/S
THE EFFECT OF PROCESS PARAMETERS ON PENETRATION IN 1
GAS METAL ARC WELDING
Lian Bin Liun1, Ahmad Zuhardi Bin Hussain
2
Experimental Study on Geometries Energy Absorption of Fiber 10
Metal Laminated Mild Steel under Axial Compression.
Muhammad Izani Sahak1, a
, Ahmad Kamely Mohamad2,
b and Abdullah Atiq Ariffin
1, c
Study On Surface Roughness and Material Removal Rate Of Dry 18
Surface Grinding Repeat Method (Mirror).
Abdul Razak Mohd Daim1,a
Kajian Mengenai Proses Mencanai Permukaan Dalam Keadaan 30
Basah Dan Kering Terhadap Keluli lembut Berkarbon Sederhana
Menggunakan Konsep Design Of Experiment (DOE). Abdul Razak Mohd Daim
1,a
IMPLEMENTATION OF LEAN CONCEPTS IN UNIMEKAR 43
METALS SDN. BHD.’s FOUNDRY SHOP SPIPZS 2012.
Ahmad Zuhardi Bin Hussain, Mohd Hasni Bin Angterian
dan Darman Bin Pawali.
EFFECT OF COMPOSITE WRAPPING ON CRASHWORTHINESS 48 1MUHAMMAD IZANI SAHAK, 2MUHAMMAD AHMAD KAMAL
THE EFFECT OF PROCESS PARAMETERS ON PENETRATION IN GAS METAL ARC
WELDING
Lian Bin Liun1, Ahmad Zuhardi Bin Hussain
2
H/p: 019-8705231 Email: [email protected]
H/p: 012-4992070 Email: [email protected]
Jabatan Kejuruteraan Mekanikal
Politeknik Kota Kinabalu
1
THE EFFECT OF PROCESS PARAMETERS ON PENETRATION IN GAS METAL ARC
WELDING
Lian Bin Liun1, Ahmad Zuhardi Bin Hussain
2
H/p: 019-8705231 Email: [email protected]
H/p: 012-4992070 Email: [email protected]
Jabatan Kejuruteraan Mekanikal
Politeknik Kota Kinabalu
ABSTRACT In this study, the effects of various welding parameters on welding penetration of Stainless Steel tube having 2.5
mm wall thickness welded by robotic gas metal arc welding (GMAW) were investigated. The welding current, arc
voltage and welding speed were chosen as variable parameters. The depth of penetration were measured for each
specimen after the welding operations and the effects of these parameters on penetration were analyzed. The
welding currents were 95, 105, and 115Amp, arc voltage were 14, 16, and 18V and the welding speeds were 10,
30, and 50 cm/min. As a result, increasing welding current will increase the depth of welding penetration. In
additions, arc voltage was another parameter affecting the increased in penetration. However, it effect was least
significant as compared to current. The highest penetration was observed in 10 cm/min welding speed.
Keywords: Gas Metal Arc Welding, Welding Parameters, Design of Experiment
1.0 Introduction Gas metal arc welding (GMAW) process is an important component in many industrial operations. The
(GMAW) welding parameters are important considerations for design and manufacturing engineer in the
fabrication industry.
Therefore, these parameters affecting the arc and welding bath should be estimated and their changing
conditions during process must be known in order to obtain optimum results. Former are welding current, arc
voltage and welding speed, and later are torch angle, free wire length, nozzle distance, welding direction, position
and the flow rate of gas.
Basically, sufficient penetration, high heating rate and right welding profile occur in the quality of welding
joint. These are affected from welding current, arc voltage, welding speed and protective gas parameters. Among
all, welding current intensity has the strongest effect on melting capacity, weld seals size and geometry and depth
of penetration.
When all parameters are held constant, weld seal area expands with increasing voltage. Relatively low
welding speeds cause accumulation of welding metal, large welding bath and so low penetration. The deepest
penetration values are obtained in optimum values of welding speed.
1.1 Problem Statement
Study was done by the manufacturer, but detailed study is not disclosed to the public review and not all
types of material available covered. Performance of Stainless Steel tube welded by (GMAW) welding process was
the focus of this studies and it will cover variables for parameters that are welding current, voltage and speed.
1.2 Objectives of Research
a. To study the effect of (GMAW) welding variable; welding current, arc voltage and welding speed on welding
penetration, of Stainless Steel tube.
b. To determine the most significant factor that influences penetration and welding geometry in (GMAW)
welding.
c. To suggest the best set of parameters for (GMAW) welding on Stainless Steel tube.
1.3 Significance of Research
Area of study in these researches was:
a. To study the welding quality of stainless steel tube using robotic (GMAW) arc welding.
b. To investigate the penetration, bead height and bead width of welded Stainless Steel tube by using gas metal
(GMAW) arc welding.
2.1 Literature Review
The GMAW welding process is a welding process which yields coalescence of metals heating with a
welding arc between a continuous filler metal electrode and the workpiece. The continuous wire electrode which is
drawn from a reel by an automatic wire feeder and then fed through the contact tip inside the welding torch is
melted by the internal resistive power and heat transferred from the welding arc. Heat is concentrated by the
welding arc from the end of the melting electrode to the molten weld pool and by the molten metal that is being
transferred to the weld pool (Kim et. al, 2003).
Firstly applied this technique to the GMAW welding process and investigated relationship between the
process variables and bead geometry. These results showed that arc current has the greatest influence on bead
geometry, and that mathematical models derived from experimental results can be used to predict bead geometry
accurately. (Yang et al, (1993), (Karadeniz et. al, 2007).
Study by GMAW welding parameters are the most important factors affecting the quality, productivity and
cost of welding joint (Kim et. al, 2003), (Ming et. al, 2003).
The selection of the welding procedure must be specific to ensure that an adequate clad quality is obtained (Kim et.
al, 2001).
According to the effect of process parameters on weld penetration in gas metal arc welding processes was
studied by (Karadeniz et. al, 2007). Has extended their study to the weld deposit area and presented the effects of
electrode polarity, extension and diameter, welding current, arc voltage, travel speed, power source setting and flux
basicity on the weld deposited area (Kim et. al, 2003).
2.2 Stainless steel
Stainless steel has many desirable characteristics which can be exploited in a wide range of construction
applications. It is corrosion-resistant and long-lasting, making thinner and more durable structures possible. It
presents architects with many possibilities of shape, colour and form, whilst at the same time being tough,
hygienic, adaptable and recyclable. (Baddoo, 2008).
2.2.1 Welding of stainless steel
In each case, the appropriate welding parameters were for the production of air-pressure tubes from
stainless steel sheets having 2.5mm thicknesses by using GMAW robotic arc welding were as shown in Figure 2.1.
Figure 2.1: The welded pipe analysed in the study. (Sattari and Javadi, 2008)
2.3 Effect of parameters in welding process
Voltage (V), Current (I) and Speed (S) are variables used as treatment variables for the experiment. In the
arc welding process increase in welding speed causes decrease in the heat input per unit length of the weld,
decrease in the electrode burn off rate and decrease in the weld reinforcement.
2.5 Welding Bead Geometry
The weld bead geometry which affects the load carrying capacity of the weldments and number of passes
needed to fill the groove of a joint. The bead geometry (figure 2.3) is specified by bead width, reinforcement,
penetration, penetration shape factor and reinforcement form factor.
Figure 2.3: A schematic illustration of bead geometry (Yang et. al, 2003)
3.1 Methodology The effects of process parameters on top bead width have been studied using the robotic GMAW welding.
Process parameters such as pass number, welding speed, welding current and arc voltage influence top bead width
for GMAW welding process.
3.2 Experiments. For the experimental studies, Stainless steel (Erdemir Steel) specimens having 60 × 30 × 2.5mm were used
as base-metal. This unalloyed steel is used in the production of pressure tubes. In addition, 1.2 mm diameter
electrode was used as filling metal. Gas metal arc welding operations were performed by means of a
DAIHEN Model Dr-4000 welding robot having a working capacity of 0–500 A and 0–50 V ranges. The welding
opening was fixed as 0.8 mm and the torch was centred. The welding robot and its apparatus were shown in Figure
3.1.
Figure 3.1: The welding robot and its apparatus used in experiments.
3.3 The Experimental Set-Up
The experimental set-up comprises a welding power source, a robot carrying a welding torch, a fixture, a
welding table, and an industrial personal computer (PC) for sampling and recording the welding current and
voltage. The welding current is measured by a Hall effects transducer. The welding voltage channel is connected to
the welding torch (electrode) and the base metal (work piece) by the low-pass filter with a voltage divider and peak
clipper. The current and voltage signals are continuously sampled by the computer at a sampling frequency of 100
kHz.
3.4. Design of Experiment
In order to ensure more accurate, less costly and more efficient experiments, the experiment were done by
the specific design of experiments (DOE). In this research, the experimental is design by applying a full factorial
design (2k), where k is the number of controlled variables in the experiment. There are three controlled variables
investigated for the experiment namely; welding current, arc voltage and welding speed. The welding parameters
and their level that designed to investigates were shown in Table 3.2 and Table 3.3.
Table 3.2 Process parameters and the level Control factors Parameter Low High
95 Welding current 95 Ampere 115 Ampere
105 Arc voltage 14 Volt 18 Volt
115 Welding speed 10 cm/min 50 cm/min
Table 3.3 Full factorial 2
3design matrix
Std Run Block Factor 1
A: Current Amp
Factor 2
B: Voltage B
Factor 3
C: Welding Speed
3 1 1 95 18 10
11 2 1 105 16 30
5 3 1 95 14 50
6 4 1 115 14 50
8 5 1 115 18 50
1 6 1 95 14 10
2 7 1 115 18 10
10 8 1 105 16 30
4 9 1 115 18 10
7 10 1 95 18 50
9 11 1 105 16 30
The number of level is 2 levels of each factor were selected for the 2
3 experiment is welding current, arc
voltage and welding speed, depth of penetration result welding operation. The design matrix for the 23 experiment
is shown in Table 3.3. For the DOE, 3 factorial points, and added centre point repeated 3 times. So, there are 8
samples were conducted for arc voltage. The total samples had been run on these experiments were 11 samples. A
common experimental design is one with all input factors set at two levels each. These levels are called `high' and
`low' or `+1' and `-1', respectively. A design with all possible high or low combinations of all the input factors is
called a full factorial design in two levels.
3.5 Data Analysis
Design Expert software analyse were used to find the best welding parameter in robotic arc welding using
GMAW stainless steel.
3.6 Measurement of Penetration
The GMAW specimens were exposed to metallographic investigation prior to macro-structure survey
which was the tool for the penetration by a new vision program in 10x magnification. The resulted photographs
were given in appendix B and the light of Macro-structure photos, reliable bead height and depth of penetration
values were obtained in configurations shown in appendix A.
4.1 RESULTS This chapter presents the experimental results and discussion on the effect of welding parameter (current,
voltage and welding speed) on welding bead width, welding bead height and welding penetration. The
experimental plans for the process employed full factorial design and analyzed by Analysis of variance (ANOVA).
The experimental trials involve three factors and two levels 23 experimental designs, factors involved were welding
current, welding voltage, and welding speed. The analysis for the research is based on the bead width, bead height
and welding penetration as an output response. For the full factorial experimental design, it employed with 11
experiments (8 specimens for randomize experiment) and added with 3 specimens as the centre point of the
welding parameter.
4.2 Experimental Parameter and Data
Design Expert software version 6.0 has been used to design the experimental runs and helped to analyze
the responses. The details of the factors and its level are given in Table 4.1 Factor and levels (23experimental
designs)
Table 4.1 Factor and levels (2
3experimental designs)
Factor
Coded
Name High
Coded Factor Units Type
Low level
(-1)
Centre
point (0)
High level
(+1)
A Current Ampere Numeric 95 105 115
B Voltage Volt Numeric 14 16 18
C Welding speed cm/min Numeric 10 30 50
Table 4.2 Experimental trial designed by design expert software applied randomization for welding.
Std Run Block Factor 1
A: Current Amp
Factor 2
B: Voltage B
Factor 3
C: Welding Speed
3 1 1 -1 1 -1
11 2 1 0 0 0
5 3 1 -1 -1 1
6 4 1 1 -1 1
8 5 1 1 1 1
1 6 1 -1 -1 -1
2 7 1 1 -1 -1
10 8 1 0 0 0
4 9 1 1 1 -1
7 10 1 -1 1 1
9 11 1 0 0 0
4.3 Experimental Result
There experiment specimens were 11 in total, with different welding current, arc voltage and welding
speed combinations were performed and the depth of penetration is measured for all cases. The results were
tabulated as in Table 4.3 below.
Table 4.3 Experimental Results of Robotic GMAW welding
Std Run
Welding
Current (Ampere)
Arc
Voltage (Volt)
Welding
Speed (cm/mm)
Bead Width
(mm)
Penetration
(mm)
Bead Height
(mm)
3 1 95 18 10 5.05 3.35 2.11
11 2 105 16 30 4.98 3.05 2.84
5 3 95 14 50 5.09 2.87 2.82
6 4 115 14 50 5.01 3.01 2.80
8 5 115 18 50 5.08 3.32 2.79
1 6 95 14 10 5.06 3.38 2.1
2 7 115 14 10 5.07 3.9 2.09
10 8 105 16 30 4.98 3.06 2.83
4 9 115 18 10 5.09 3.36 2.05
7 10 95 18 50 5.05 2.84 2.98
9 11 105 16 30 4.98 3.05 2.84
4.4 Factor that influences welding penetration
Based on the ANOVA analysis Table 4.4, A; represent welding current, B; represent welding voltage and
C; welding speed are the significant factor to determined the highest value penetration in GMAW welding.
ANOVA analysis proved that the model is significant with F value is 0.0003. The significant factor identified by
value that achieved probability below than 0.05.
Table 4.4 also shows that, the value of R-Squared is 0.9999 which represent 99% of the variable that has
been described by the model selected and adjusted R-Squared achieved 99.96%. The difference between R-squared
and adjusted R-squared is about 0.03% shows in small difference, referred that only significant term included in
the model.
Analysis from ANOVA clearly shows that in GMAW welding, all three selected parameter are the main
effects in determining welding penetration. To further analysis of the result, a graphic plot as shown in figure 4.17
has been used based on normal probability plot of effect. In figure 4.17 the graphical plot clearly support the
ANOVA analysis identified the significant factor where C, welding speed is the most far away from normal plot
followed by A, welding current and B, welding voltage. From the analysis, it shows that the most significant
parameter in GMAW welding is welding speed followed by welding current and then welding voltage.
Table 4.4 ANOVA table for welding penetration
Response: Penetration
ANOVA for Selected Factorial Model
Analysis of variance table [Partial sum of squares] Sum of Mean F
Source Squares DF Square Value Prob > F
Model 0.83 7 0.12 3575.79 0.0003 significant
A 0.16 1 0.16 4873.50 0.0002 B 0.011 1 0.011 337.50 0.0029
C 0.47 1 0.47 14113.50 < 0.0001
AB 4.050E-003 1 4.050E-003 121.50 0.0081 AC 1.250E-003 1 1.250E-003 37.50 0.0256
BC 0.092 1 0.092 2773.50 0.0004
ABC 0.092 1 0.092 2773.50 0.0004 Curvature 0.087 1 0.087 2596.41 0.0004 significant
Pure Error 6.667E-005 2 3.333E-005
Cor Total 0.92 10
Std. Dev. 5.774E-003 R-Squared 0.9999
Mean3.20 Adj R-Squared 0.9996
C.V.0.18 Pred R-Squared N/A
PRESS N/A Adeq Precision 202.975
4.6 Factor that influences welding geometry
For analysis of welding geometry (bead height), the ANOVA analysis shows that the experimental model
is significant with Probe >F is 0.0002. All three factors are listed to be significant, welding current, welding
voltage and welding speed are listed as main effect for the model, each of them are represented by probability
0.0034, 0.0180 and 0.0001 respectively as shown in Table 4.5.
Table 4.5 ANOVA table for welding geometry (bead height)
Response: Bead height ANOVA for Selected Factorial Model
Analysis of variance table [Partial sum of squares]
Sum of Mean F Source Squares DF Square Value Prob >F
Model1.18 7 0.17 5062.07 0.0002
A 9.800E-003 1 9.800E-003 294.00 0.0034 B 1.800E-003 1 1.800E-003 54.00 0.0180
C 1.16 1 1.16 34656.00 < 0.0001 AB 6.050E-003 1 6.050E-003 181.50 0.0055
AC 2.450E-003 1 2.450E-003 73.50 0.0133 BC 4.050E-003 1 4.050E-003 121.50 0.0081
ABC 1.800E-003 1 1.800E-003 54.00 0.0180
Curvature 0.30 1 0.30 8920.41 0.0001 Pure Error 6.667E-005 2 3.333E-005
Cor Total 1.48 10
Std. Dev. 5.774E-003 R-Squared 0.9999
Mean2.57 Adj R-Squared 0.9997
C.V.0.22 Pred R-Squared N/A
PRESSN/A Adeq Precision 178.081
4.7 The best parameter setting in GMAW welding
In the numerical optimization test, the desired goals for the factors and response were set using the feature
provided by Design Expert Software.
Table 4.6 The best solution as suggest by Design Expert
Solutions
Num Current Voltage Speed Penetration height Desirability 1 115.00 14.00 10.00 3.89999 2.09 0.978 Selected 2 115.00 14.01 10.00 3.89797 2.08985 0.977
3 114.56 14.00 10.00 3.88851 2.09022 0.973
4 115.00 14.37 10.00 3.84851 2.08626 0.956 5 112.33 14.00 10.00 3.83061 2.09133 0.945
6 115.00 14.00 12.65 3.84103 2.13704 0.925
7 107.15 14.00 10.00 3.69587 2.09392 0.877 8 96.06 17.27 10.00 3.36052 2.10548 0.680
8 Solutions found
Using Design Expert software, there are seven solutions offers as shown in table 4.6 with desirability
above 0.9 in GMAW welding and the selected best combination solution with regards to the overall objective,
penetration and bead geometry were expected to achieve the maximum value of 3.89999 mm with 0.978
desirability value as the first suggested solution. The best parameter setting to get the highest penetration value in
GMAW welding was combination of welding setting at welding current is 115.00 Ampere, welding voltage is
14.00 Volt and welding speed is 10.00 cm/min.
5.1 DISCUSSION The effect of welding current on penetration as stated in chapter 4 was commented according to the table
4.3, the depth of penetration is increase with the increasing of welding current. It can be seen that the penetration
increase with the increment of welding current for 14, 16, and 18 V values. The biggest penetration value was
obtained as 3.38mm in 115 A and 14 V condition, while the smallest one as 2.84 mm in 95 A and 18 V. (Karadeniz
et. al, 2007).
5.2 Factor that influences welding penetration and welding geometry
The result is different with (Karadeniz, 2007) finding which state that the effect of welding current
approximately 2.5 times greater than that of arc voltage and welding speed on penetration. The possible reason for
the different result are the range of arc voltage and welding speed used in this experiment is different with the
experiment done by (Karadeniz, 2007) and due to the working capacity of robotic GMAW welding machine used
in this study is different with previous study.
5.3 The best parameter setting in GMAW welding
The best parameter for GMAW welding obtained using Design Expert software analysis. The selected
combination of the best parameter setting is obtains from the highest value of desirability, in this case the highest
desirability value is 1.000. The combination factor for the best parameter in GMAW; welding speed is 10 cm/min,
welding current is 115 A and arc voltage is 14V.
From the best selected parameter, it is observed that in order to obtain the highest depth of penetration, the
welding speed must be set to minimum, and welding current must be in maximum. These result is agree with the
finding of previous research. Base on (Karadeniz, 2007) study, it stated that to obtain high depth of penetration in
GMAW welding, welding current should be completed at high welding current and low welding speed.
REFERENCES
Baddoo.N.R, (2008). Journal of contruction steel research; November 2008, pages 1199-1206 international
stainless steel expert seminar.
E.Karadeniz et. al, (2007). Modenesi PJ, Avelar RC. The influence of small variations of wire characteristics on
gas metal arc welding process stability. J Mater Process Technology 1999;86:226–32.
Kim IS et al. (2003). A study on relationship between process variables and bead penetration for robotic CO2
arc welding. J Mater Process Technol;136:139–45.
Ming HG et al. (2003). Acquisition and pattern recognition of spectrum information of welding metal transfer.
Mater Des;24:699–703.
Yang LJ et al.(1993). The effects of process variables on the weld deposit area of submerged arc welds. Weld
J;72:11–8.
Kim. Ill-Soo; Son, Joon-Sik; and Jeung, Young-Jae, (2001). "Control and optimisation of bead width for nmlti-
pass welding in robotic arc welding processes." Australasian Welding Journal (v46, 3rd
qtr), pp43-46.
Experimental Study on Geometries Energy Absorption of Fiber Metal Laminated Mild Steel under Axial Compression
Muhammad Izani Sahak1, a, Ahmad Kamely Mohamad2, b and Abdullah Atiq Ariffin1, c
1Department of Mechanical Engineering, Politeknik Kota Kinabalu Sabah, 88450, Malaysia
2Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76109, Malaysia
[email protected], [email protected], [email protected]
10
Experimental Study on Geometries Energy Absorption of Fiber Metal Laminated Mild Steel under Axial Compression
Muhammad Izani Sahak1, a, Ahmad Kamely Mohamad2, b and Abdullah Atiq Ariffin1, c
1Department of Mechanical Engineering, Politeknik Kota Kinabalu Sabah, 88450, Malaysia
2Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76109, Malaysia
[email protected], [email protected], [email protected]
Keywords: Energy absorption, Fiber metal laminated mild steel, Circular and square tube, Axial compression
Abstract. Crashworthiness is the ability of a structure to protect its occupants during an impact.
Depending on the nature of the impact and the vehicle involved, different criteria are used to
determine the crashworthiness of the structure. The combination of metal and composite layers
is known to displays plastics deformation and failure mode composite layered. The capable of
structures to absorb large amount of energy are great interest in an effort to reduce the impact of
collision. In this experimental study, an investigation will be carried out on geometries behavior
of fiber metal laminated mild steel under axial compression. For structures subjected to
compression, energy absorption is highly desirable and will depend on its physical shape. The
efficiency is measured in term of the absorption performance that is higher in hybrid composites
than in metallic and composite structures. Much of the working assessing the energy absorbing
capability of composite materials and structures under compressive loading has been to a greater
extent restricted to axis metric tubes. Therefore, it will contribute knowledge on how to design
hybrid composite material tubes to develop a stable or controlled compression response under
sustained axial loading.
Introduction
Energy absorption capacities play an important factor for engineers in designing
structures for transportation vehicles such as automobiles, trains, and airplanes. Higher safety
requirements for vehicles are being demanded to protect passengers involved in accidents.
Structures of the vehicle must absorb sufficient energy and reduce the impact load even when the
vehicle collides with each other at high velocities. Many materials used in designing
crashworthy structures are rate sensitive were energy absorption capability is dependent on the
speeds at which they are crushed [1] and the axial displacement of the tubes [2]. Thin wall tubes
have been used as impact energy absorbers due to its behavior of progressively buckle like
bending plastic hinges to absorb energy under axial low-velocity impacts. The peak axial loads
in the impact test were approximately constant under the range of testing velocities, and therefore
several geometries of thin-walled circular tubes can be predicted by the ones in the static tests
[3]. The most common shapes are circular, square and rectangular and these tubes are used as
front and side impact beams in vehicles. Experimental and analytical results have shown that
energy absorption depend on various tube parameters such as geometry, material properties,
boundary, length [4], thickness [5,6] and loading conditions of the tubes where it buckle in
different modes of deformation, namely concertina, diamond and Euler collapsing modes.
Taking consideration of these design parameters, and its methods can improve energy absorption
characteristics of the tubes under axial loads significantly [7]. It is also found out that the
specific energy absorption for circular tube is higher than square and rectangular tubes [8].
Composite structures in the other hand have a wide range of applications because of their
high stiffness and strength with respect to their weight. It also provides ductile, and a stable
plastic collapse mechanism as they progressively deform which eventually increases the energy
absorption during collision of the vehicles [9]. Composite structures could stand high loads and
provide a significant increase in the energy absorption when compared to similar metal
structures. The energy absorption capability of composite structures is dependent upon the
mechanism by which the structures collapse.
The E-glass fiber/resin composite tubes reinforced by carbon fiber have a significant
increase in energy absorption when collision compared to the fully glass fiber/epoxy tubes [10].
The impact force displacement relationships of E-glass fiber/resin composites increased due to
increasing impact energy of great specimen deflection related with significant membrane
tensions [11]. In recent years, fiber composite materials have been increasingly used in the
development of advanced metal shell structures. Due to their superior strength-to-weight ratio,
hybrid structures are excellent for energy absorption and have been extensively used in such
engineering structures. As a result, several researchers have recently addressed metal tubes that
are wrapped with a fiber-reinforced plastic composite where overwrapping the metal tubes with
composite is an effective means of increasing energy absorption capacity and improving the
crushing characteristics of such tubes [12].
Specimen Fabrication
Commercially available conventional mild steel (CMS) were prepared according to the
required shape, size, and quantity (refer Fig. 1). The dimensions of the conventional mild steel
(CMS) were given in Table 1. The E-glass fiber/polyester resin laminated mild steel (LMS)
specimens were fabricated by hand lay-up process. Scratches were made over the outer shell
surface of the conventional mild steel (CMS) specimen with fine sand paper (Grade 800) for
better adhesion between mild steel metal surface and E-glass fiber/polyester resin laminate.
Three sets of laminated mild steel (LMS) were overwrapped on the outer surface of the
conventional mild steel (CMS) by hand lay-up method to form a laminated mild steel (LMS) or
hybrid shell. Percentage of glass fiber on the composite is maintained at 60%. The specimen
will then left to cure for about five hours at room temperature and the thickness of the shell was
maintained at 2.60-3.70 mm. The specimens are shown in Fig.2 and the dimensions of the
hybrid shells are given in Table 2.
Fig. 1 Geometrical details of (a) conventional mild steel (CMS), (b) laminated mild steel (LMS).
(a)
(b)
No Ni
No Ni
No Ni
No Ni
t1 t1
t2 t2
(a) (b)
Fig. 2 Conventional mild steel (CMS) and laminated mild steel (LMS) for (a) Circular shape, and
(b) Square shape.
Table 1 Dimensions of conventional mild steel (CMS) specimens.
Model Shape
Inner
diameter/
base
length
(Ni)(mm)
Outer
diameter/
base
length
(No)(mm)
Height
(Hc)(mm)
Mild steel
thickness
(average)
(t1)(mm)
Total thickness
(average)
t = (t1 + t2)(mm)
CMS1 Circular 44.84 48.04 120 1.6 1.6
CMS2 Square 47.04 50.24 120 1.6 1.6
CMS3 Circular 44.27 48.07 120 1.9 1.9
CMS4 Square 46.27 50.07 120 1.9 1.9
Table 2 Dimensions of laminated mild steel (LMS) specimens.
Model Shape
Inner
diameter/
base
length
(Ni)(mm)
Outer
diameter/
base
length
(No)(mm)
Height
(Hc)(mm)
Mild steel
thickness
(average)
(t1)(mm)
Composite
laminate
thickness
(average)
(t2)(mm)
Total thickness
(average)
t = (t1 + t2)(mm)
LMS1 Circular 44.84 50.30 120 1.6 2.73 4.33
LMS2 Square 47.04 53.40 120 1.6 3.18 4.78
LMS3 Circular 44.27 50.90 120 1.9 3.32 5.22
LMS4 Square 46.27 53.60 120 1.9 3.67 5.57
Experimental Setup
The axial compression test was conducted on samples with the cross head speed of 5
mm/min on a Universal Testing Machine (UTM) of 20 ton capacity and it is integrated with the
load displacement data recordable device. The specimens are placed in coaxial between top and
bottom rigid platen and proper seating is ensured. The axial load is applied progressively from
top end of
truncated specimen. The mode of collapse of conventional mild steel (CMS) and laminated mild
steel (LMS) was observed and also corresponding load displacement dataset were recorded up to
80 mm axial compression of the specimen. Three specimens were tested for each category of
samples to ensure the repeatability of the results. The load displacement curve obtained from the
experiment for conventional mild steel (CMS) and laminated mild steel (LMS) is shown in Fig.
3a and b respectively. The energy absorption capabilities of the specimens were estimated from
the area under the load displacement characteristic curves.
(a) (b)
Fig. 3 Load displacement curve for (a) conventional mild steel (CMS) and (b) laminated mild
steel (LMS).
Results and Discussion
The axial compression loading experiment on conventional mild steel (CMS) and
laminated mild steel (LMS) were then studied. From the analysis, it was observed that the top
end of the specimen shell initially buckles towards outward where the specimens moves laterally
and shortens under a load it can no longer support when it undergoes quasi-static axial
compression loading. Due to continuous loading, the specimen deforms further by rolling plastic
mode of collapse and generates stationary hinges. It was observed that the formation of number
of stationary hinges were always in perpendicular to the direction of loading. The main failure
mechanisms that contribute to energy dissipation in the case of unstable brittle collapse mode are
buckling of tube wall, crack propagation, and splitting of the tube wall where metal absorb most
of the energy in the plastic deformation mode.
In the load displacement curve (Fig. 3), the rise and fall of load denotes the influence of
stationary hinges and plastic collapse of failure. In order to analyses the change of energy
absorption levels, the specimens were grouped into four different categories based on their shape,
thickness and height as shown in Table 3. To study the effect of specimens geometrical on the
load displacement curve for the benefit of higher energy absorption capability, the load
displacement curve obtained from experimental results were considered from specimens under
Group 2 and Group 4 of Table 3. The specimens belong to this group having different geometry
but same in shell thickness and height. The load displacement curve obtained from experimental
of Group 2 and Group 4 specimens are shown in Fig. 4. It was observed that for specimens
under Group 2 (CMS3 & LMS3) will have higher energy absorption capability compared to
specimens under Group 4 (CMS4 & LMS4). These prove that circular tube specimen gains
higher energy absorption compared to square tube specimen.
Table 3 Groups of specimens based on shape, thickness and height.
Group Specimen model Shape Mild steel thickness
(average)(mm) Height (mm)
Group 1 CMS1 & LMS1 Circular 1.6 120
Group 2 CMS3 & LMS3 Circular 1.9 120
Group 3 CMS2 & LMS2 Square 1.6 120
Group 4 CMS4 & LMS4 Square 1.9 120
(a) (b)
Fig. 4 Load displacement curve for (a) conventional mild steel (CMS) and (b) laminated mild
steel (LMS) under different geometries but same in thickness and height.
Conclusion
The energy absorption capacity of conventional mild steel (CMS) and laminated mild
steel (LMS) shell were analyses by experimental methods. The modes of failure and load
displacement graphs were extracted from experimental data. The performance in terms of energy
absorption rate of the specimen was observed by the load displacement curve. Both conventional
mild steel (CMS) and laminated mild steel (LMS) specimens shows similar trend in load
displacement curve but the laminated mild steel (LMS) has higher initial crush and greater
average load than conventional mild steel (CMS). The geometries of both conventional mild
steel (CMS) and laminated mild steel (LMS) also contribute to the capability of specimens in
absorbing energy where the circular specimens gains higher crushing performance compared to
square specimens. The E-glass fiber/polyester resin laminated mild steel (LMS) shows higher
initial collapse load, higher average load, and high ultimate peak load than of conventional mild
steel (CMS) specimens and it absorbs more energy. The ability of this family of hybrid to absorb
more energy due to combination of two materials with different properties that is significantly
better than any materials currently on the market.
Acknowledgment
The authors gratefully acknowledged Department of Polytechnic Education,
Ministry of Higher Education Malaysia for all the support and fund and to all the
technical support from the Mechanical Engineering Department’s research members and
Research Unit of Politeknik Kota Kinabalu, Sabah.
References
[1] S. Ramakrishna, and H. Hamada, Energy Absorption Characteristic of Crashworthy
Structural Composite Materials, Key Engineering Material. Vol. 141-143 (1998) pp. 585-620.
[2] M. Miyazaki, and H. Negishi, Deformation and Energy Absorption of Aluminum Square
Tubes with Dynamic Axial Compressive Load, Material Transaction. Vol. 44(8) (2003) pp.
1566-1570.
[3] M. Higuchi, S. Suzuki, and T. Adachi, Dynamic Axial Crushing of Circular Tubes
Subjected to High Velocity Impact, 2nd
International Symposium on Experimental Mechanics.
(2012).
[4] S. Ataollahi, S. T. Taher, R. A. Eshkoor, A. K. Ariffin, and C. H. Azhari, Energy
Absorption and Failure Response of Silk/Epoxy Composite Square Tubes: Experimental,
Composite Part B: Engineering. Vol. 43(2) (2012) pp. 542-548.
[5] A. M. S. Hamouda, R. O. Saied, and F. M. Shuaeib, Energy Absorption Capacities of
Square Tubular Structures, Journal of Achievements in Materials and Manufacturing
Engineering. Vol. 24(1) (2007).
[6] A. Dadrasi, An Investigation on Crashworthiness Design of Aluminium Columns with
Damage Criteria, Research Journal of Recent Sciences. Vol. 1(7) (2012) pp. 19-24.
[7] S. Salehghaffari, M. Tajdari, and F. Mokhtarnexhad, Attempts to Improve Energy
Absorption Characteristics of Circular Metal Tubes Subjected to Axial Loading, Thin-Walled
Structures. Vol. 48 (2012) pp. 379-390.
[8] R. Velmurugan, and R. Muralikannan, Energy Absorption Characteristics of Annealed
Steel Tubes of Various Cross Sections in Static and Dynamic Loading, Latin American Journal
of Solids and Structures. Vol. 6 (2009) pp. 385-412.
[9] M. Kathiresan, K. Manisekar, and V. Manikandan, Performance analysis of fibre metal
laminated thin conical frusta under axial compression, Composite Structures. Vol. 94 (2012) pp.
3510-3519.
[10] K. Asad, Finite Element and Experimental Analysis for the Performance of Hybrid
Composite Tubes under Crushing. Pakistan Journal of Applied Sciences. Vol. 1(3) (2001) pp.
438-442.
[11] A. Kersys, N. Kersiene, and A. Ziliukas, Experimental Research of the Impact Response
of E-Glass/Epoxy and Carbon/Epoxy Composite Systems, Materials Science. Vol. 16(4) (2010)
pp. 1392-1320.
[12] Y. S. Tai, M. Y. Huang, and H. T. Hu, Numerical Modeling of Steel-Composite Hybrid
Tubes Subject to Static and Dynamic Loading, World Academy of Science, Engineering and
Technology. Vol. 65 (2012).
Study On Surface Roughness and Material Removal Rate Of Dry
Surface Grinding Repeat Method (Mirror)
Abdul Razak Mohd Daim
1,a
1Dept. of Mechanical Engineering, Politeknik Kota Kinabalu, Jalan
Politeknik, 88450 Sapanggar, Kota Kinabalu, Sabah, Malaysia.
18
Study On Surface Roughness and Material Removal Rate Of Dry
Surface Grinding Repeat Method (Mirror)
Abdul Razak Mohd Daim1,a
1Dept. of Mechanical Engineering, Politeknik Kota Kinabalu, Jalan
Politeknik, 88450 Sapanggar, Kota Kinabalu, Sabah, Malaysia.
ABSTRACT
Grinding process is the finishing process in a process of smoothing the surface to
get the lowest surface roughness by removing a small amount of material on the surface
of the work piece. The purpose of this study is to find the most significant cutting
parameters on surface roughness and MRR(Material Removal Rate) in one conditions,
namely by dry. By using the repeat method (mirror) the data was analyzed using Design
Expert software version 6 with the analysis of variance ( ANOVA ) to analyzed the data
obtained such as surface roughness and MRR. The study found that the most significant
cutting parameter for the surface roughness in the dry condition velocity table with F
value 0.0112. For Material Removal Rate (MRR), the velocity table is the main cutting
parameter in dry conditions with value 0.0008. Results of the study to obtain surface
roughness is, velocity table give most influence on the surface roughness in dry
conditions.
Key words : Surface Grinding, Cutting parameter, Full factorial, surface roughness and
Material Removal Rate.
1.0 INTRODUCTION
Surface grinding process is a final machining process producing a product. According to
Malkin S [9], grinding is the most common collective name for a process that uses hard
abrasives particles as cutting medium. At present, the grinding process is a major
manufacturing accounts for about 20-25% of total operating expenses machining in
industrial countries.
Rising raw materials in China led to a high demand. Strong demand in China's economy
is stable enough to produce more than one hundred million kg (more than 200 million
pounds) of steel products per year. Most of gray cast iron is reserved for military use in
crafting weapons and armor soldiers, but some have been used for many steel products,
such as fashion car cylinder head, block, iron, motors and much more is needed to fill the
growing demand in the real market.
Less energy is used when we can get a cut depth in the grinding process. The industry
uses grinding process such as automotive, aircraft, shipbuilding, engines, turbines and
others can benefit from it. The grinding process is necessary to produce accurate and
precise measurements. It also aims to create a better quality of surface condition he not
only benefit the industry but also improve the quality of the material.
Type parameter in the grinding process will affect the characteristics of the workpiece,
such as surface roughness, temperature, energy and others. There are many types of
parameters in the grinding process. Surface quality produced in the grinding surface is
influenced by various parameters such as the parameter wheel, workpiece parameters,
process parameters and machine parameters in writing Mustafa [11].
In this study, researchers conducted a study of gray cast iron after a surface grinding
process cutting parameters for the relationship of the surface roughness and material
removal rate. Other researchers parameters which is controlled, such as machinery,
grinding wheels, skill workers, materials, machine calibration and the like. Cutting
parameters studied were cutting depth, feed rate and cutting speed table and use a dry
grinding. Using a different example, it can determine which have a significant parameter
to the workpiece surface roughness and material removal rate.
Surface finishing and metal removal rate is greatly influenced by cutting parameters.
Interaction in cutting parameters such as cutting depth, feed rate and cutting speed table
are various parameters to be considered for production of a product that has a proper
surface, saving materials, and energy costs and help the delivery of products to
customers on time due to the selection of cutting parameters the correct and appropriate.
[3,5,8,10].
Thus the study of an experimental and data analysis using Design Expert Software
Version 6. Experiment shaped multi factor will be analyzed by ANOVA variance cutting
parameters studied as described by Henderson [2]. Selection of the proper combination
of cutting parameters can produce surface finish that meets the standards prescribed
standard.
2.0 METHODOLOGY
In this experiment using design of experiment (DOE), which is 23 by 8 work piece
Repeat to use and apply the method (mirror). Repeat method (mirror) will make the
work piece is rolled into as many as 16 overall number of work piece. 2 values in the
DOE shows minimum and maximum values in coordinating one variable, while the
third, namely the index of the value 2 indicates the number of variable cutting
parameters studied in the experiment. Variable cutting parameters studied were as table
velocity, depth of cut and feed of rate. Selection of experimental design requires
knowledge of the process to be carried out and the choice of factors and levels may
significantly affect the response of materials, by article Zurita et al [12]. Gray studied
material is cast iron (SAE G29000 F10008), this material is widely used in the
production of vehicle components. In this study is to obtain the best cutting parameters
of the material being studied. Grinding machine used is a brand Seedtex 52 Model A1S.
Machine calibration has been performed which includes works such as balancing,
dressing and leveling. Spark has also set out a total of 5 times each time the spark out of
the feed rate is done. Similarly, work is also done every time dressing for the grinding of
each work piece with step 7, 5,3 and 1. The diamond is used for grinding stainless 2.5
sized grinding wheel for every new piece work. From Table 1 shows the Design Matrix
is used in this study which included 16 specimens. The equation of full factorial design
is stated in Equation 1.
Full Factorial Equation = 2k
(1)
Where k denotes as the number of factors, i.e., depth of cut, feed of rate and velocity
table being investigated in this experiment and 2 is level of experiment, i.e., low(-1) and
high (+1). The analysis of ANOVA is employed in order to indicate the mathematical
models of Surface Grinding machining characteristic using design expert software
version 6. Table 2 shows the setting parameters for Surface grinding machine.
Table 1 : Combination parameter in arrays Design Matrix ( 23 ) – Two Level
Fig. 1 : Surface Grinding Machine Seedtex Model 52A1S
All of the grinding experiments were carried out on a Surface Grinding Machine,
Model YSG 52 A1S manufactured by Seedtex Precision Machinery in Taiwan
Fig 1.
Table 2 : Experimental parameters setting for Surface Grinding Machine
From Table 2 shows the Design Matrix is used in this study which included 16
specimens.
3.0 RESULT AND DISCUSSION
3.1 Significant Ra and MRR
Analysis of Variance (ANOVA) for Surface Roughness : Three parameter cutting of
surface roughness (Ra) in dry condition analysis are given in the design expert, there are
Feed of rate, Depth Of Cut and Velocity Table.
Fig. 2 : ANOVA for surface roughness (Ra) in dry condition
The result are significant Prob>F = (0.0209). According to data analysis of variance
table (ANOVA), The values of (Prob>F) less than 0.0500 indicate model terms are
significant. While, values more higher than 0.1000 indicate the model term are not
significant. The most effect of parameter surface grinding are velocity table, c with the
values Prob >F (0.0112), shown on Fig.2
Factor Low ( - 1) High (+ 1)
Velocity table (m/s) 4 12
Feed of rate (mm/s) 0.50 1.00
Depth of cut (μm) 10.00 20.00
Feed of rate
movement
Verification of Mathematical Model for Ra : Verification of mathematical models for
each response was performed in order to ensure whether the predicted value that given
by software is correct or not. Calculation was carried out using the equation given by
software. The calculation was based on the parameters used in the confirmation test in
running on sample 4 as shown in table 3. Verification on Ra equation in term of coded
factor generated by design expert software is shown in Equation 2.
Ra = 0.19 + 1.87 x 10-4
x A + 3.812 x 10-3
x B – 0.033 x C + 0.020 x A x B – 0.043 x A
x C – 6.562 x 10-3
x B x C + 3.437 x 10-3
x A x B x C
(2)
Where :
Factor A = 1, B = 1, C = -1
Hence ;
Ra = 0.19 + 1.87 x 10-4
x (1) + 3.812 x 10-3
x (1) – 0.033 x (-1) + 0.020 x (1) x (1) –
0.043 x (1) x (-1) – 6.562 x 10-3
x (1) x (-1) + 3.437 x 10-3
x (1) x (1) x (-1)
Ra = 0.19 + 0.000187 + 0.003812 + 0.033 + 0.020 +0.043 + 0.006562 – 0.003437 =
0.2931 𝜇m
Percentage of difference between calculated value and experimental value of Ra is 2%
as indicated in Equation 3. It is confirmed that mathematical model generated by Design
Expert software is reliable and acceptable.
(3)
Confirmation differential between calculated and experimental similar trend shows
table 3. It is confirmed that experimental result is acceptable.
Analysis of Variance (ANOVA) for MRR : Three parameter cutting of Material
Removal Rate (MRR) in dry condition analysis are given in the design expert, there
are Feed of rate, Depth Of Cut and Velocity Table.
Fig. 3 : ANOVA for Material Removal Rate (MRR) in dry condition.
From Fig. 3 shows, result are significant Prob>F = 0.0032. According to data analysis of
variance table (ANOVA), The values of (Prob>F) less than 0.0500 indicate model terms
are significant. While, values more higher than 0.1000 indicate the model term are not
significant. The most effect of parameter surface grinding are velocity table, c with the
values Prob >F (0.0008). According by Klocke and Eisenblatter [6] the dry grinding using
wheel was also investigated with high cutting speed and for external cylindrical grinding.
It is found that with increasing the grinding speed it is possible to increase the mass
removal rate in the grinding process.
From Table. 3 shows, Ra value of the minimum is no specimen. 14 ie 0.086 um and the
highest was 0.3 um specimen no. 2. While the highest MRR no.9 specimen of 1.005 mg /
second and the lowest value of 0.019 mg / second specimen no. 6.
Ra value obtained from the average of the three readings of surface roughness machine
utilization. While the MRR is from equation 4 as shown below.
𝑀𝑅𝑅 =𝑊𝑎−𝑊𝑏
tm (mg/second) (4)
Where :
Wa = Material weight before machining
Wb = Material weight after machining
tm = Machining Time
Table 3: Result Ra and MRR for dry grinding
3.2 Mean Analysis Ra and MRR
Surface Roughness (Ra)
From Anova analysis, mean value of A is 1.052, B is 0.15 and C is 10.75. The higher
percentage of parameter cutting surface roughness (Ra) is C (velocity table) 89.5%,
second higher is A (feed of rate) 8.8% and the lower is B (depth of cut) 1.3%, shown Fig.
4.
Material Removal Rate (MRR).
From Anova analysis, mean value of A is 20.68, B is 3.01 and C is 27.15. The higher
percentage of parameter cutting surface roughness (Ra) is C (velocity table) 53.4%,
second higher is A (feed of rate) 40.7% and the lower is B (depth of cut) 5.9%, shown
Fig. 5.
Fig.4 : F Value parameter cutting Surface Roughness (Ra)
Fig. 5 : F Value interaction parameter cutting Surface Roughness (Ra)
According by Kamal et al [4], it says that the mass removal rate (MRR) is mainly
affected by cutting speed and feed of rate of dry grinding process. With the increase in
cutting speed the mass removal rate is increase. The paramter considered in the
experiment are the best parameter cutting process to attain maximum mass removal rate.
3.3 The best value parameter cutting setting
The selected value of the best parameter cutting setting is number 1, it use 0.55 feed of
rate, 10.00 depth of cut and 12.00 velocity table. Another selected method is surface
roughness 0.215403 μm, material removal rate (MRR) 0.196454 mg/sec and desirability
0.782. This can be referred to Fig. 6 the software has been analyzed as below.
Fig. 6 : The best value parameter cutting setting
4.0 CONCLUSION
4.1 Surface Roughness Dry Condition
The analysis for dry surface roughness has determined that the most effective of grinding
surface is velocity table with prob > 0.0112 and the percentage is 89.5%. It has proven
through 16 specimen repeated method with average of surface roughness 0.05μm. From
the main effect plotted, it is observed that there is decrease of surface roughness when
the parameter for velocity table is decrease. The percentages value affecting of surface
roughness are in the following order. Feed of rate (8.8%), depth of cut (1.3%) and
velocity table (89.5%). Velocity table are significant for cutting parameter effecting
surface roughness, this fact is also supported by Babu et al [1] based on their ANOVA
velocity table are the most significant parameters for affecting multi response
characteristics. The feed of rate and depth of cut value are not significant. Based on the
curve, the reason why these two parameter cutting is not significant because of the
minimum and maximum value are not in best position to get the significant mean value.
Fig. 7 shows the adjustment of the cutting parameters that need to be adjusted for future
studies.
According by M. Kiyak and Carkib [7] study on surface roughness in External Cylinder
Grinding, researcher prove that in dry grinding process, an increase on work piece speed
will decreased surface roughness. The researcher result was opposite in the application of
cutting fluid that increase on work piece speed produced a higher surface roughness.
Fig. 7 : Mean value curve
4.2 Material Removal Rate (MRR)
In dry condition, the best cutting parameter for the output process of MRR in terms of
machining cutting parameter are velocity table, feed of rate also significant, only depth
of cut are not significant. This have been identified on cast iron on surface grinding
machine using design expert software. The values of prob>F less than 0.05 μm are
significant with the value 0.0032 μm.
5.0 REFERENCES
1. Babu Autherson. P, Sundaram . S Sivapragash. M, and Shanawaz. A.W. (2012).
"Optimizing the Process Parameters of ELID Grinding Using Grey Relation
Analysis ". Advances in Production Engineering & Management,Vol.7 pp113-122.
2. Henderson G.R, (2006). Six Sigma : Quality Improvement With MINITAB. John
Wiley & Sons. England, ISBN : 10: 0470011556. pp:452.
3. Jae-Seob Kwak(2005). "Application of Taguchi and Response Surface
Methodologies For Geomatric Error in Surface Grinding Process",
International Journal on Machine Tools and Manufacture, vol. 45, No.33 pp.
327-324.
4. Kamal Hassan, Anish Kumar and M.P Garg (2012). "Experimental Investigation of
Material Removal Rate in CNC Turning using Taguchi Method". Lecturer, Haryana
Engineering College.
5. M Janardhan and A. Gopala Krishna (2012), “Multi Objective Optimization of
Cutting Parameter for Surface Roughness and Metal Removal Rate in Surface
Grinding using Response Surface Methodology”. University College of Engineering,
JNTU, India.
6. Klocke. F and Eisenblatter (1997)."Dry cutting, Annals of the CIRP". Vol. 46/2
Pages 519-525.
7. M.Kiyak and O Carkib E Altana (2006), “Study on Surface Roughness in External
Cylinder Grinding”. Technical University, 34390 Istanbul, Turkey.
8. Maheswari S.K, Misra V and Metha N.K (1991). "A New Approach To Parameters
Selection: Integration Of Quality: Computers and Industrial Engineering". 21(1-
4), 57-62.
9. Malkin,.S. (1989), “ Grinding of metal: Theory and Application, Applied
Metalworking”. American Society for Metals, vol. 3, No. 2.
10. Muhamad Afiq bin Razali (2010), “Effect of wheel Grinder on the Surface
Roughness when Grinding Aluminium Alloy”, Faculty of Mechanical Engineering,
Universiti Malaysia Pahang.
11. Mustafa Kemal Kulekci (2012). "Surface Grinding Process Based in the Taguchi
Method". Mersin University, Turkey.
12. Zurita, O., Acosta, A. and Moreno, D. (2002). Superficial Hardening in the Plane
Grinding of 1055 - 1045 Steel, ASM International.
Kajian Mengenai Proses Mencanai Permukaan Dalam Keadaan Basah
Dan Kering Terhadap Keluli lembut Berkarbon Sederhana
Menggunakan Konsep Design Of Experiment (DOE).
Abdul Razak Mohd Daim
1,a
1Dept. of Mechanical Engineering, Politeknik Kota Kinabalu, Jalan
Politeknik, 88450 Sapanggar, Kota Kinabalu, Sabah, Malaysia.
30
Abstrak— Kemasan Akhir sesuatu permukaan yang baik adalah berdasarkan nilai yang minimum kekasaran
permukaan, diukur dalam nilai micrometer. Dalam kajian ini mesin canai permukaan jenama Seedtex telah
digunakan untuk mencanai benda kerja (keluli lembut berkarbon sederhana). Proses mencanai ini menggunakan dua
situasi itu basah dan kering. Dengan menggunakan kaedah Design of Experiment (DOE) sebanyak 16 benda kerja
telah dicanai untuk basah dan 16 lagi untuk kering. Benda kerja yang telah dicanai, diukur menggunakan alat
pengukur kekasaran permukaan untuk mendapatkan bacaan. Bagi kadar pembuangan bahan, alat penimbang
digunakan dan bagi kekerasan, alat pengukur Vickers telah digunapakai. Setelah data mentah diperolehi, data
tersebut dimasukkan ke dalam software design expert version 6.0 untuk menganalisa data secara ANOVA, bagi
mendapatkan parameter pemotongan seperti kedalaman pemotongan, kadar suapan dan halaju meja yang signifikan
dengan Ra, MRR dan Hardness. Hasil daripada kajian didapati kekasaran permukaan dan kadar pembuangan bahan
adalah signifikan iaitu kurang daripada 0.05 bagi keadaan basah dan kering. Manakala untuk kekerasan bahan tidak
signifikan dengan kerja mencanai permukaan yang hanya membuang sebahagian kecil bahan, iaitu hanya 0.005 mm.
Bagi keadaan basah dan kering untuk kekasaran permukaan, didapati mencanai permukaan secara kering lebih baik
berbanding dengan basah. Data yang diperolehi boleh digunapakai oleh pihak industri pemesinan untuk
mendapatkan nilai kekasaran permukaan yang minimum bagi meningkatkan kualiti sesuatu benda kerja (produk).
Walaubagaimanapun, untuk kajian akan datang pembolehubah parameter pemotongan perlu dilaraskan semula
seperti kadar suapan dan kedalaman pemotongan bagi mendapatkan optimization cutting parameter dalam proses
mencanai permukaan tanpa menggunakan bahan penyejuk (dry situation).
Kata Kunci : Kedalaman Pemotongan, Kadar Suapa, Halaju Meja, Kekasaran Permukaan, Kadar
Pembuangan Bahan dan kekerasan bahan.
PENGENALAN
Proses mencanai permukaan adalah satu proses akhir sesuatu produk sebelum produk tersebut dihantar ke
bahagian kualiti sebelum ianya dipasarkan. Oleh itu, pengkaji ingin memahami lagi proses ini bagi mendapatkan
kualiti permukaan bahan selepas melalui proses mencanai permukaan ini.
Proses Mencanai Permukaan adalah satu proses yang paling kompleks dalam proses pemesinan. Proses ini adalah
amat penting untuk mendapatkan ketepatan dan ukuran yang tepat untuk permukaan produk atau yang berkualiti
tinggi keadaan permukaannya [7]. Dalam kajian ini pengkaji mengkaji satu bahan iaitu keluli berkarbon sederhana
untuk memahami proses pencanaian ini. Selain itu juga, pengkaji menggunakan dua kaedah pencanaian iaitu
pemesinan menggunakan bahan penyejuk dan satu tidak menggunakan bahan penyejuk. Parameter pemotongan
(penyebab) yang dikaji adalah terdiri daripada halaju meja pemotongan, kadar suapan dan kedalaman pemotongan
terhadap bahan yang dikaji iaitu keluli lembut berkarbon sederhana. Proses Mencanai Permukaan, adalah satu proses
yang paling biasa digunakan dalam Sektor Pembuatan untuk menghasilkan kemasan licin pada permukaan yang rata,
[5]. Kualiti permukaan dan kadar pembuangan logam adalah dua ciri-ciri prestasi yang perlu dipertimbangkan dalam
proses pencanaian. Kadar penjimatan proses pencanaian bergantung kepada parameter pemotongan yang terdiri dari
kedalaman pemotongan, kadar suapan, kelajuan meja pemotongan, selain daripada itu gred roda pencanai dan sifat
bahan itu sendiri.
Oleh yang demikian juga, pengkaji ingin mengetahui adakah proses mencanai permukaan ini mempengaruhi
kekerasan bahan tersebut selepas proses pencanaian tersebut dilakukan. Maka dengan itu, pengkaji
mengklasifikasikan Parameter Pemotongan iaitu Kadar Suapan, Kedalaman Pemotongan dan Kelajuan Meja
pemotongan adalah pembolehubah tak bersandar dan Kekasaran Permukaan, Kadar Pembuangan Bahan dan
Kekerasan Bahan adalah pembolehubah yang bersandar. Dengan itu, objektif kajian ini adalah untuk :
i. Mengenalpasti parameter pemotongan yang manakah signifikan dengan Kekasaran Permukaan, Kadar
Pembuangan Bahan dan Kekerasan Permukaan.
ii. Mengenalpasti faktor utama parameter pemotongan yang mempengaruhi Benda Kerja.
Skop kajian ini, adalah untuk mengkaji benda kerja keluli lembut berkarbon sederhana, parameter pemotongan
serta proses pencanaian didalam dua keadaan basah dan kering. Dapatan kajian, diharapkan boleh digunapakai oleh
pihak industri untuk mendapatkan setting variable cutting yang dapat meningkatkan kualiti produk dan seterusnya
untuk mengurangkan waste time, energy dan sebagainya untuk memenuhi kehendak pelanggan.
METODOLOGI
Dalam kajian ini, rekabentuk eksperimen adalah menggunakan Software Design Expert Version 6 dalam
merekabentuk kajian. Kaedah ulangan digunakan untuk mendapatkan nilai kebolehpercayaan data yang tinggi dan
kesahihan maklumat semasa kajian dilakukan. Dengan mengetahui nilai tinggi dan nilai rendah setiap pembolehubah
Parameter Pemotongan, rekabentuk eksperimen dapat dilakukan. Pemilihan rekabentuk eksperimen adalah
memerlukan kefahaman yang tinggi dalam sesuatu proses yang ingin dijalankan dan pemilihan faktor dan tahap yang
ketara boleh memberi kesan kepada tindak balas sesuatu bahan, [1].
Oleh itu, daripada Jadual 1 menunjukkan Matrix Design yang digunakan dalam kajian ini memerlukan 16
spesimen. Persamaan reka bentuk Faktorial lengkap dinyatakan dalam persamaan 1.
Persamaan Faktorial Lengkap = 2k
(1)
Di mana k menandakan sebagai bilangan faktor, iaitu, kedalaman pemotongan, kadar suapan dan halaju meja
disiasat dalam eksperimen ini dan 2 adalah tahap eksperimen, iaitu, rendah (-1) dan tinggi (1). Analisis ANOVA
digunakan untuk mendapatkan nilai signifikan iaitu kurang dari 0.05 bagi Pencanaian Permukaan yang bercirikan
pemesinan menggunakan Design Expert Software versi 6. Jadual 2 menunjukkan parameter setting untuk rekabentuk
proses pencanaian permukaan. Rajah 1 menunjukkan Mesin Canai Permukaan yang digunakan.
Jadual 1: parameter Gabungan dalam tatasusunan Design Matrix (23) - Dua Tingkat
Jadual 2: Penetapan Parameter Eksperimen dalam Proses Pencanaian Permukaan.
Rajah. 1: Mesin Canai Permukaan Seedtex Model 52A1S
Dalam mendapatkan kualiti permukaan sesuatu produk, peringkat awal adalah dengan mengintegrasikan
pembolehubah parameter pemotongan seperti Kadar Suapan, Kedalaman Pemotongan dan Kelajuan Meja
Pemotongan. Parameter yang lain dianggap terkawal seperti kecekapan mesin, kemahiran individual, roda pencanai
dan penentukuran pemesinan [4]. Hasil kajian, mendapati dengan melakukan kadar suapan yang rendah kualiti
permukaan sesuatu produk dapat ditingkatkan, [9]. Ini bermakna kadar suapan yang tinggi akan meningkatkan nilai
kekasaran permukaan sesuatu spesimen. Penggunaan perisian yang bersesuaian akan membantu merekabentuk
Factor Low ( - 1) High (+ 1)
Velocity table (m/s) 4 12
Feed of rate (mm/s) 0.50 1.00
Depth of cut (μm) 10.00 20.00
eksperimen dan seterusnya mengoptimumkan proses dan produk yang ingin dihasilkan, [8]. Dengan bantuan
perisian seperti Design Expert dapat membantu membuat analisa secara ANOVA iaitu signifikan parameter
pemotongan terhadap kekasaran permukaan. ANOVA digunakan untuk mengenalpasti pembolehubah yang paling
penting dan untuk mengetahui kesan interaksi parameter, [2]. Pemilihan kombinasi yang betul dalam pemilihan
parameter pemesinan akan menghasilkan kemasan permukaan dan kadar penyingkiran logam yang diingini, [3].
DAPATAN KAJIAN
Hasil kajian ini boleh dikategorikan kepada tiga bahagian utama, iaitu kesan parameter pemotongan terhadap
bahan iaitu kekasaran permukaan, yang keduanya kesan kadar pembuangan bahan dan yang ketiga adalah kekerasan
bahan selepas melalui proses pencanaian permukaan. Bahagian Pertama : Berikut adalah hasil eksperimen yang
telah dibuat selepas melakukan pemesinan dan ujikaji makmal seperti yang ditunjukkan pada Jadual 3 di bawah, tanpa
bahan penyejukan. Jadual 4 di bawah menunjukkan hasil analisa ANOVA bagi kesan parameter pemotongan
terhadap kekasaran permukaan (kering) dan Rajah 3(a), 3(b) dan 3(c) adalah menunjukkan graf yang berkaitan
Parameter Pemotongan dengan nilai Ra (roughness average) berkeadaan kering.
Jadual 3 : Hasil Data Eksperimen Selepas Pemesinan dan Ujikaji Makmal (kering).
Jadual (4) : Analisa ANOVA di antara parameter pemotongan dengan kekasaran permukaan tanpa bahan penyejuk.
3(a) : Kadar Suapan
3 (b) : Kedalaman Pemotongan
3 (c) : Halaju Meja
Rajah 3(a), 3(b) dan 3(c) adalah menunjukkan graf yang berkaitan Parameter Pemotongan dengan nilai Ra (roughness average) berkeadaan kering.
Seterusnya hasil dapatan bahagian Parameter Pemotongan yang menggunakan bahan penyejukan (basah) terhadap
kekasaran permukaan (Ra) mendapati kadar suapan adalah siginifikan dengan nilai 0.0385. Berikut adalah hasil
eksperimen yang telah dibuat selepas melakukan pemesinan dan ujikaji makmal seperti yang ditunjukkan pada Jadual
5 di bawah, dengan menggunakan bahan penyejukan. Jadual 6 menunjukkan hasil analisa ANOVA bagi kesan
parameter pemotongan terhadap kekasaran permukaan (basah) dan Rajah 4(a), 4(b) dan 5(c) adalah menunjukkan graf
yang berkaitan Parameter Pemotongan dengan nilai Ra (roughness average) berkeadaan basah.
Jadual 5 : Hasil Data Eksperimen Selepas Pemesinan dan Ujikaji Makmal (basah).
Jadual (6) : Analisa ANOVA di antara parameter pemotongan dengan kekasaran permukaan dengan bahan penyejuk.
Rajah 4 (a) : Kadar Suapan
Rajah 4 (b) : Kedalaman Pemotongan
Rajah 4 (c) : Halaju Meja
Rajah 4(a), 4(b) dan 4(c) adalah menunjukkan graf yang berkaitan Parameter Pemotongan dengan nilai Ra (roughness average) berkeadaan basah.
Bahagian Kedua (MRR) kadar pembuangan bahan : Berikut adalah hasil dapatan kajian selepas proses
pemesinan dan ujikaji makmal bagi keadaan kering (tanpa bahan penyejukan) iaitu analisa ANOVA seperti yang
ditunjukkan pada Jadual 7 di bawah.
Jadual 7 : Analisa ANOVA bagi Parameter Pemotongan terhadap MRR
Rajah 5 : Graf menunjukkan MRR melawan Halaju Meja yang signifikan.
Graf MRR melawan halaju meja adalah pembolehubah parameter pemotongan yang signifikan dengan MRR bagi
proses pemesinan tanpa menggunakan bahan penyejukan seperti yang ditunjukkan seperti pada Rajah 5 di atas.
Jadual 8 di bawah pula adalah hasil analisa ANOVA bagi proses pemesinan dengan menggunakan bahan
penyejuk (basah).
Jadual 8 : Analisa ANOVA bagi parameter pemotongan terhadap MRR (basah)
Rajah 6 (a) dan (b) di bawah menunjukkan pembolehubah parameter pemotongan iaitu kedalaman pemotongan
dan halaju pemotongan yang signifikan dengan MRR bagi proses pemesinan yang menggunakan bahan penyejukan.
Rajah 6 (a) : Kedalaman Pemotongan
Rajah 6 (b) : Halaju Meja
Rajah 6 (a) dan (b) : MRR melawan kedalaman pemotongan dan halaju meja yang signifikan dalam proses pemesinan (basah).
Bahagian Ketiga iaitu pembolehubah parameter pemotongan terhadap kekerasan permukaan bahan. Jadual 9 di
bawah menunjukkan pemesinan berkeadaan kering.
Jadual 9 : Analisa ANOVA parameter pemotongan terhadap kekerasan permukaan bagi proses pemesinan kering
Bagi proses pemesinan yang menggunakan bahan penyejukan seperti yang ditunjukkan pada Jadual 10 di antara
Parameter Pemotongan dengan kekerasan permukaan bahan.
Jadual 10 : Analisa ANOVA parameter pemotongan terhadap kekerasan permukaan bagi proses pemesinan basah
PERBINCANGAN DAN RUMUSAN
Hasil daripada kajian yang dibuat dapatlah dibincangkan bahawa bagi ketiga-tiga pembolehubah yang bersandar
yang terdiri daripada Kekasaran Permukaan (Ra), Kadar Pembuangan Bahan (MRR) dan Kekerasan Permukaan
didapati hanya dua pembolehubah yang signifikan terhadap Parameter Pemotongan iaitu (Ra) dan (MRR). Di antara
(Ra) pula yang dibahagikan kepada dua iaitu proses pemesinan kering dan basah didapati pemesinan kering yang
signifikan dengan model F iaitu 0.026 iaitu kurang daripada 0.05 mengikuti ketetapan analisa ANOVA yang telah
dibuat. Ini menunjukkan dapatan kajian ini selari dengan M.Kiyak et. al [6], iaitu hasil daripada proses pemesinan
kering didapati dengan peningkatan kelajuan meja pemotongan kualiti kekasaran permukaan dapat ditingkatkan dan
jika menggunakan proses pemesinan dengan bahan penyejukan pula adalah sebaliknya. Selain itu, bagi pemesinan
kering didapati kedalaman pemotongan adalah paling sedikit mempengaruhi kekasaran permukaan dengan peratus
8.5% berbanding kadar suapan (18.8%) dan halaju meja (72.7%). Kenyataan ini selari dengan Taranvir Singh et.al
[10], dalam kajian tersebut mendapati bahawa kedalaman pemotongan adalah parameter yang paling kurang
mempengaruhi kekasaran permukaan berbanding parameter yang lain seperti saiz bijian roda pencanai, halaju meja,
halaju roda pencanai dan sebagainya.
Sementara itu pula, Kadar Pembuangan Bahan (MRR) juga signifikan untuk kedua-dua proses pemesinan basah
dan kering. Menurut M. Janardhan dan A.Gopala Krishna [5], menyatakan bahawa peningkatan kadar halaju meja
pemotongan akan meningkatkan kadar pembuangan bahan. Ini boleh dilihat pada analisa ANOVA, mendapati
bahawa pada proses pemesinan basah model F adalah bernilai 0.0073 iaitu lebih rendah daripada 0.05 mengikut
piawai yang ditetapkan. Bagi pemesinan kering pula pembolehubah parameter pemotongan iaitu halaju meja adalah
signifikan terhadap kadar pembuangan bahan.
Bagi pembolehubah bersandar iaitu kekerasan permukaan bahan selepas proses pemesinan kering dan basah
yang melalui pelbagai interaksi pembolehubah yang tak bersandar didapati tidak signifikan. Ini kerana proses
pemesinan permukaan adalah proses kerja kemasan akhir yang mana kedalaman pemotongan adalah sangat kecil
yang kedalaman yang minimum untuk mesin yang digunakan ini adalah 0.005 micrometer.
PENUTUP
Dengan itu, dapat disimpulkan bahawa untuk kekasaran permukaan dan kadar pembuangan bahan adalah
signifikan dengan parameter pemotongan, manakala kekerasan pula adalah sebaliknya. Kajian akan datang untuk
mendapat Optimization Cutting Parameter pembolehubah seperti kedalaman pemotongan dan kadar suapan perlu
dilaraskan semula untuk mendapati setting yang terbaik bagi meningkatkan lagi kualiti permukaan dan seterusnya
produktiviti sesuatu produk dapat ditingkatkan disamping mengurangkan waste time, waste energy dan sebagainya.
Proses pencanaian permukaan yang melalui proses pencanaian kering menjadi keutamaan.
Rujukan
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Vibration”, INT J MACH, 41(4), 2001, pp.509-520.
[2] Henderson G.R, (2006). Six Sigma : Quality Improvement With MINITAB. John Wiley & Sons, Englan, ISBN : 10:
0470011556, pp: 452.
[3] Jae-Seob Kwak (2005). “Application of Taguchi and Response Surface Methodologies for Geometric Error in Surface
Grinding Process”, International Journal oh Machine Tools and Manufacture, Vol. 45, No.3, pp. 327-324.
[4] Maheshwari S.K Misra V. and Metha N.K (1991). “A New Apporoach To Parameters Selection: Integration Of
Quality; Computers and Industrial Engineering”.
[5] M. Janardhan and A. Gopala Krishna (2012).” Multi-Objective Optimization of Cutting Parameter for Surface
Roughness and Metal Removal Rate in Surface Grinding Using Response Surface Methodology”. University College
of Engineering, JNTU. India.
[6] M. Kiyak, and O Carkib E Altana (2006). “Study on Surface Roughness in External Cylinder Grinding”. Techical
University, 34390 Istanbul, Turkey.
[7] Mohd Ifwat Bin Jomrah, Muhammad Firdaus bin Apdal, Nazrin bin Mirhan, Mohd Nazreen bin Jamaldin, and Rizwan
bin Gapar (2012). “Comparison Study on Surface Roughness of Dry and Wet Surface Grinding”. Center Point Method
Politeknik Kota Kinabalu, Sabah.
[8] Mustafa Kemal Kulekci (2012). “Analysis of Process Parameters for a Surface-Grinding Process Based in the Taguchi
Method”. Mersin University, Turkey.
[9] P.Chockalinham, and Lee Hong Wee. (2012). “Surface Roughness and Tool Wear Study on Milling of AISI 304
Stainless Steel Using Different Cooling condition.” Multimedia University, Melaka, Malaysia.
[10] Singh. T, Kumar. P, & Goyal. K (2014). “Optimization of Process Parameters for Minimum Out-of-Roundness
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