Available online at www.sciencedirect.com<br />
<br />
ScienceDirect<br />
Procedia Technology 14 (2014) 204 – 210<br />
<br />
2nd International Conference on Innovations in Automation and Mechatronics Engineering,<br />
ICIAME 2014<br />
<br />
Effect and Optimization of Machine Process Parameters on MRR<br />
for EN19 & EN41 materials using Taguchi<br />
tool steel<br />
<br />
Vikasa, Shashikanta, A.K.Royb and Kaushik Kumarb*<br />
b<br />
<br />
a<br />
Research Scholar, Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, 835215, India<br />
Associate Professor, Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, 835215, India<br />
<br />
Abstract<br />
<br />
The present work deals with the comparison of the MRR for EN19 and EN41 material in a die sinking EDM<br />
machine. The various input factors like Pulse ON time, Pulse OFF time, Discharge current and voltage were<br />
considered as the input processing parameters, while the MRR is considered as the output. Optimization using<br />
Taguchi method was performed to predict the best combination of inputs towards maximum output. A comparison<br />
was done to obtain the effect of these input parameters over the MRR for both the material, and simultaneously the<br />
impact of the carbon percentage over the MRR was investigated. It was found that the Discharge current in case of<br />
the EN41 material and EN19 material had a larger impact as compare to other processing parameters on the MRR. A<br />
relative study of the carbon composition for both the material was also done.<br />
© 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license<br />
© 2014 The Authors. Published by Elsevier Ltd.<br />
(http://creativecommons.org/licenses/by-nc-nd/3.0/).<br />
Selection and/or peer-review under responsibility of the Organizing Committee of ICIAME 2014.<br />
Peer-review under responsibility of the Organizing Committee of ICIAME 2014.<br />
Keywords: EN19, EN41, EDM, MRR,Taguchi, Design of Experiments, Optimization<br />
<br />
* Corresponding author. Tel.: +91-9431597463.<br />
E-mail address: kkumar@bitmesra.ac.in<br />
<br />
1. Introduction<br />
In an EDM process, choosing the correct parameter for finding out the Optimized value of MRR is very important.<br />
Different input parameters like Pulse-ON time, Pulse-OFF time, Discharge current and Voltage affects the MRR for<br />
both EN19 and EN41 material in a different manner. Apart from these input parameters, there are many other<br />
parameters, which affect the MRR differently. They may be flushing pressure, feed rate, etc. A lot of work has been<br />
carried out in this field for the optimization of the MRR with different materials and in the presence of different<br />
<br />
2212-0173 © 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license<br />
(http://creativecommons.org/licenses/by-nc-nd/3.0/).<br />
Peer-review under responsibility of the Organizing Committee of ICIAME 2014.<br />
doi:10.1016/j.protcy.2014.08.027<br />
<br />
Vikas et al. / Procedia Technology 14 (2014) 204 – 210<br />
<br />
methods. Vikas et al (2013) carried out the optimization of the MRR for EN41 material based on the 4 input<br />
parameters like the pulse on time, pulse off time, discharge current and gap voltage. He found out that the current<br />
along with the pulse-off time had a larger impact over the MRR followed by some of the interaction plot, while the<br />
affect of the other parameters were negligible. Kamal Hassan et al (2012) carried out the same optimization<br />
technique using Taguchi to optimize the MRR for medium brass alloy in CNC turning machine. He used the various<br />
input parameters like cutting speed, depth of cut, feed, etc to optimize the MRR. He found that the cutting speed and<br />
the feed rate had significant effect over the MRR followed by their interaction. He found that the cutting speed and<br />
the feed rate had direct effect over the MRR, as they increased directly with them. Similarly, Kuldeep ojha et al<br />
(2010) and AKM Asif Iqbal et al (2010) also carried out the improvement of the MRR on the different input<br />
parameters. Many researcher (Bhaduri et al (2009), Belgassim and Abusada (2012), Ikram et al (2013), Natrajan<br />
and Arunachalam (2011), Tiwari (2013), Sanchez et al (2002), Singh et al (2004), Kurnia et al (2008), Jahan et al<br />
(2009), and Antony (2001)) have worked with different materials and on different non conventional machines using<br />
different parameters to obtain most optimized value in order to economize the outputs.<br />
<br />
Nomenclature<br />
C1<br />
C2<br />
C3<br />
C4<br />
A<br />
B<br />
C<br />
D<br />
<br />
Pulse-On time for EN19 material<br />
Pulse-Off time for EN19 material<br />
Discharge Current for EN19 material<br />
Voltage for EN19 material<br />
Pulse-On time for EN41 material<br />
Pulse-Off time for EN41 material<br />
Discharge Current for EN41 material<br />
Voltage for EN41 material<br />
<br />
2. Experimental Setup<br />
The entire experiment was carried on a Die sinking EDM machine (Electronica EMT-43 Machine). Experiment<br />
was performed individually for both the materials one after another. The work-piece on which the EDM process was<br />
carried out was EN19 and EN41 material of cylindrical crossTool for EDM operation was a rectangular positive polarity Copper of dimension 25x25mm. Paraffin oil was<br />
selected as the dielectric medium. First of all the initial weight of the work-piece was taken before carrying out the<br />
EDM operation. The final weight was then compared with the initial weight and the difference of the two weights<br />
yield the MRR for the EN material. The experiment was carried out according to the design of experiment table<br />
generated by the taguchi design of experiments. For each set of experiments, the value of all the 4-input parameters<br />
were made constant and accordingly, the material removal was carried out in the EDM machine. The process was<br />
repeated for all the 27 experiments. The percentage composition of the different elements were obtained by Energy<br />
Dispersive X-Ray Spectroscopy (EDX) (JSM 63901v, Resolution=3nm at 30kV at high vaccum mode and 4nm at<br />
40 kV low vaccum mode). The numbers of levels are selected by dividing the total span of available values of each<br />
of the input parameters in three parts namely Lower level, medium level and the upper level. The Taguchi design of<br />
experiments is constructed on the basis of the same. A set of 4-input values of A, B, C, D, C1, C2, C3 and C4 were<br />
considered and depicted in the table below:<br />
<br />
205<br />
<br />
206<br />
<br />
Vikas et al. / Procedia Technology 14 (2014) 204 – 210<br />
Table I: Design factor along with their levels:<br />
<br />
Variable<br />
<br />
Coding for<br />
EN41<br />
<br />
Coding for<br />
EN19<br />
<br />
Level<br />
<br />
1<br />
Pulse ON<br />
Time(Ton)<br />
<br />
A<br />
<br />
2<br />
<br />
3<br />
<br />
200<br />
<br />
300<br />
<br />
400<br />
<br />
C1<br />
<br />
Pulse OFF time<br />
(Toff)<br />
<br />
B<br />
<br />
2300<br />
<br />
2200<br />
<br />
2100<br />
<br />
C2<br />
<br />
Discharge<br />
current (Ip)<br />
(Amp)<br />
<br />
C<br />
<br />
8<br />
<br />
16<br />
<br />
24<br />
<br />
C3<br />
<br />
Gap voltage (V)<br />
(Volt)<br />
<br />
D<br />
<br />
40<br />
<br />
60<br />
<br />
80<br />
<br />
C4<br />
<br />
Table II: Chemical composition of EN 41 Tool Steel<br />
<br />
Element<br />
<br />
App Conc.<br />
<br />
Intensity<br />
Corrn.<br />
<br />
Weight%<br />
<br />
Weight%<br />
Sigma<br />
<br />
Atomic%<br />
<br />
CK<br />
<br />
2.36<br />
<br />
0.5005<br />
<br />
9.02<br />
<br />
2.23<br />
<br />
22.97<br />
<br />
OK<br />
<br />
13.86<br />
<br />
1.2359<br />
<br />
21.48<br />
<br />
1.44<br />
<br />
41.07<br />
<br />
Cr K<br />
<br />
1.01<br />
<br />
1.1053<br />
<br />
1.76<br />
<br />
0.43<br />
<br />
1.03<br />
<br />
Fe K<br />
<br />
29.95<br />
<br />
0.9322<br />
<br />
61.46<br />
<br />
2.07<br />
<br />
33.67<br />
<br />
Eu L<br />
<br />
2.95<br />
<br />
0.8966<br />
<br />
6.29<br />
<br />
1.30<br />
<br />
1.27<br />
<br />
TOTAL<br />
<br />
100<br />
<br />
Table III: Chemical composition of EN 19 Tool Steel<br />
<br />
Element<br />
<br />
App Conc.<br />
<br />
Intensity<br />
Corrn.<br />
<br />
Weight%<br />
<br />
Weight%<br />
Sigma<br />
<br />
Atomic%<br />
<br />
CK<br />
<br />
2.45<br />
<br />
0.5073<br />
<br />
13.67<br />
<br />
3.03<br />
<br />
30.75<br />
<br />
OK<br />
<br />
9.25<br />
<br />
1.1469<br />
<br />
22.79<br />
<br />
1.48<br />
<br />
38.50<br />
<br />
Fe K<br />
<br />
20.58<br />
<br />
0.9142<br />
<br />
63.54<br />
<br />
2.49<br />
<br />
30.75<br />
<br />
TOTAL<br />
<br />
100<br />
<br />
3. Result and Discussion :<br />
3.1 Taguchi Method: The Taguchi method of optimization is a 3-step process (Jameson (2001), Montgomery<br />
(2001)), which deals with the selection of raw material at the first stage, based on the engineering properties of that<br />
material. At the 2nd stage, the optimization process is carried out on the basis of the design of experiment table. The<br />
3rd stage is the stage, where the comparison between the experimental and the predicted values are done to validate<br />
the result.<br />
On the basis of the different combinations of inputs obtained by the Taguchi method, the corresponding S/N ratio<br />
was generated for both the materials individually by the use of Minitab 16 software (Minitab Manual 2010).<br />
Table IV: Experimental Results:<br />
<br />
207<br />
<br />
Vikas et al. / Procedia Technology 14 (2014) 204 – 210<br />
<br />
A<br />
(TON)<br />
<br />
B<br />
(TOFF)<br />
<br />
C<br />
(IP)<br />
<br />
D<br />
(V)<br />
<br />
EN41<br />
<br />
EN19<br />
<br />
MRR<br />
(gm/min)<br />
<br />
S/N<br />
Ratio(dB)<br />
<br />
MRR<br />
(gm/min)<br />
<br />
S/N<br />
Ratio(dB)<br />
<br />
1<br />
1<br />
<br />
1<br />
1<br />
<br />
1<br />
2<br />
<br />
1<br />
2<br />
<br />
7.222222<br />
12.05263<br />
<br />
17.17342<br />
21.62164<br />
<br />
5.1956<br />
9.6296<br />
<br />
14.3127<br />
19.6722<br />
<br />
1<br />
1<br />
1<br />
1<br />
1<br />
1<br />
1<br />
2<br />
2<br />
2<br />
2<br />
2<br />
2<br />
2<br />
2<br />
2<br />
3<br />
3<br />
3<br />
3<br />
3<br />
3<br />
3<br />
3<br />
3<br />
<br />
1<br />
2<br />
2<br />
2<br />
3<br />
3<br />
3<br />
1<br />
1<br />
1<br />
2<br />
2<br />
2<br />
3<br />
3<br />
3<br />
1<br />
1<br />
1<br />
2<br />
2<br />
2<br />
3<br />
3<br />
3<br />
<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
1<br />
2<br />
3<br />
<br />
3<br />
2<br />
3<br />
1<br />
3<br />
1<br />
2<br />
2<br />
3<br />
1<br />
3<br />
1<br />
2<br />
1<br />
2<br />
3<br />
3<br />
1<br />
2<br />
1<br />
2<br />
3<br />
2<br />
3<br />
1<br />
<br />
16.53125<br />
7.380952<br />
14.1<br />
31<br />
7.827586<br />
24.9<br />
31.96<br />
5.569767<br />
11.18182<br />
24.63889<br />
6.090909<br />
20.2766<br />
27.82759<br />
11.30435<br />
21.0625<br />
29<br />
4.693878<br />
15.9322<br />
23.24<br />
9.142857<br />
17.25532<br />
23.72727<br />
8.949153<br />
17.43137<br />
41.73333<br />
<br />
24.36611<br />
17.36225<br />
22.98438<br />
29.82723<br />
17.87256<br />
27.92399<br />
30.09214<br />
14.91674<br />
20.97025<br />
27.83242<br />
15.69364<br />
26.1399<br />
28.88951<br />
21.06491<br />
26.4702<br />
29.24796<br />
13.43064<br />
24.04551<br />
27.32472<br />
19.22164<br />
24.73846<br />
27.50496<br />
19.03564<br />
24.82663<br />
32.40966<br />
<br />
13.7146<br />
4.5641<br />
11.6657<br />
26.3242<br />
4.4659<br />
21.4438<br />
28.4438<br />
2.4438<br />
7.4437<br />
20.2521<br />
3.6310<br />
16.5551<br />
21.2836<br />
16.4579<br />
18.3849<br />
24.4432<br />
2.2377<br />
11.4052<br />
19.4559<br />
6.4533<br />
12.4428<br />
18.8812<br />
4.3619<br />
13.4438<br />
35.4438<br />
<br />
22.7437<br />
13.1871<br />
21.3383<br />
28.4071<br />
12.9982<br />
26.6260<br />
29.0797<br />
7.7611<br />
17.4358<br />
26.1294<br />
11.2004<br />
24.3787<br />
26.5609<br />
24.3275<br />
25.2892<br />
27.7632<br />
6.9962<br />
21.1421<br />
25.7810<br />
16.1957<br />
21.8983<br />
25.5206<br />
12.7935<br />
22.5704<br />
30.9908<br />
<br />
After the generation of the above table, the Response table for Mean S/N ratio for both the materials were<br />
obtained, on the basis of which the corresponding the rank of the different parameters were used to find the level of<br />
importance towards affecting the MRR.<br />
Table V: Response table for Mean S/N ratio for EN41:<br />
Level<br />
1<br />
2<br />
3<br />
Delta<br />
Rank<br />
<br />
A<br />
(TON)<br />
23.25<br />
23.47<br />
23.62<br />
0.37<br />
4<br />
<br />
B<br />
(TOFF)<br />
21.3<br />
23.6<br />
25.44<br />
4.14<br />
2<br />
<br />
C<br />
(IP)<br />
17.31<br />
24.41<br />
28.61<br />
11.3<br />
1<br />
<br />
D<br />
(V)<br />
25.07<br />
23.38<br />
21.88<br />
3.19<br />
3<br />
<br />
Mean<br />
(A+B+C+D)/4<br />
21.7325<br />
23.715<br />
24.8875<br />
<br />
Table VI: Response table for Mean S/N ratio for EN19:<br />
Level<br />
1<br />
2<br />
3<br />
Delta<br />
Rank<br />
<br />
C1<br />
(TON)<br />
13.939<br />
14.544<br />
13.792<br />
0.752<br />
4<br />
<br />
C2<br />
(TOFF)<br />
18.543<br />
13.533<br />
10.198<br />
8.346<br />
2<br />
<br />
C3<br />
(IP)<br />
5.535<br />
13.602<br />
23.138<br />
17.603<br />
1<br />
<br />
C4<br />
(V)<br />
17.726<br />
13.446<br />
11.103<br />
6.623<br />
3<br />
<br />
Mean<br />
(A+B+C+D)/4<br />
13.93575<br />
13.78125<br />
14.5575<br />
<br />
208<br />
<br />
Vikas et al. / Procedia Technology 14 (2014) 204 – 210<br />
<br />
The graphs were then plotted on the basis of the response table so obtained. From the graph, the optimized value<br />
for EN41 material was obtained at A3B3C3D1; While, the optimal condition for EN19 material were found out at [C1]3 [C2]1 [C3]3 [C4]1.<br />
<br />
Fig1: S/N plot for EN41 and EN19 material<br />
<br />
The ANOVA table, also called the Analysis of Variance table was then generated using the Minitab software.<br />
The ANOVA table is the table showing the importance of the different parameters towards the MRR. The entire<br />
result was confirmed at 95% confidence level and in both the cases, it was found out that Current followed by the<br />
Pulse-off time and voltage had larger impact over the MRR. However, the Pulse-ON time and the interaction of<br />
parameters did not have any impact over the MRR.<br />
Table VII: ANOVA Results for EN41:<br />
Source<br />
<br />
DOF<br />
<br />
A<br />
<br />
2<br />
<br />
B<br />
<br />
2<br />
<br />
C<br />
<br />
2<br />
<br />
Seq SS<br />
<br />
Adj SS<br />
<br />
Adj MS<br />
<br />
F<br />
<br />
4.66<br />
<br />
4.66<br />
<br />
2.33<br />
<br />
0.66<br />
<br />
296.96<br />
<br />
296.96<br />
<br />
148.48<br />
<br />
41.78*<br />
<br />
1831.31<br />
<br />
1831.31<br />
<br />
915.65<br />
<br />
257.64*<br />
24.23*<br />
<br />
D<br />
<br />
2<br />
<br />
172.23<br />
<br />
172.23<br />
<br />
86.12<br />
<br />
A*B<br />
<br />
4<br />
<br />
17.08<br />
<br />
17.08<br />
<br />
4.27<br />
<br />
12<br />
<br />
A*C<br />
<br />
4<br />
<br />
11.73<br />
<br />
11.73<br />
<br />
2.93<br />
<br />
0.82<br />
4.51<br />
<br />
B*C<br />
<br />
4<br />
<br />
64.10<br />
<br />
64.10<br />
<br />
16.02<br />
<br />
Error<br />
<br />
6<br />
<br />
21.32<br />
<br />
21.32<br />
<br />
3.55<br />
<br />
Total<br />
<br />
26<br />
<br />
2419.39<br />
<br />
Significant at 95% confidence level(*F0.05,2,6=19.33)<br />
<br />
Table VIII: ANOVA Results for EN19:<br />
Source<br />
C1<br />
C2<br />
C3<br />
C4<br />
C1*C2<br />
C1*C3<br />
C2*C3<br />
Error<br />
Total<br />
<br />
DOF<br />
<br />
Seq SS<br />
<br />
Adj SS<br />
<br />
Adj MS<br />
<br />
2<br />
2.861<br />
2.861<br />
1.431<br />
2<br />
317.625<br />
317.625<br />
148.48<br />
2<br />
1397.705<br />
1397.705<br />
915.65<br />
2<br />
203<br />
203<br />
101.500<br />
4<br />
11.774<br />
11.774<br />
2.944<br />
4<br />
33.698<br />
33.698<br />
8.424<br />
4<br />
31.715<br />
31.715<br />
7.929<br />
6<br />
27.532<br />
27.532<br />
4.589<br />
26<br />
2025.911<br />
Significant at 95% confidence level(*F0.05,2,6=19.33)<br />
<br />
F<br />
0.31<br />
34.61*<br />
152.3*<br />
22.12*<br />
0.64<br />
1.84<br />
1.73<br />
<br />
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