Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30685
Modeling and Analysis of Process Parameters on Surface Roughness in EDM of AISI D2 Tool Steel by RSM Approach

Authors: M. K. Pradhan, C. K. Biswas

Abstract:

In this research, Response Surface Methodology (RSM) is used to investigate the effect of four controllable input variables namely: discharge current, pulse duration, pulse off time and applied voltage Surface Roughness (SR) of on Electrical Discharge Machined surface. To study the proposed second-order polynomial model for SR, a Central Composite Design (CCD) is used to estimation the model coefficients of the four input factors, which are alleged to influence the SR in Electrical Discharge Machining (EDM) process. Experiments were conducted on AISI D2 tool steel with copper electrode. The response is modeled using RSM on experimental data. The significant coefficients are obtained by performing Analysis of Variance (ANOVA) at 5% level of significance. It is found that discharge current, pulse duration, and pulse off time and few of their interactions have significant effect on the SR. The model sufficiency is very satisfactory as the Coefficient of Determination (R2) is found to be 91.7% and adjusted R2-statistic (R2 adj ) 89.6%.

Keywords: response surface methodology, ANOVA, surface roughness, central composite design, electrical discharge machining

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072621

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1953

References:


[1] R. Snoeys, F. Staelens, and W. Dekeyser, "Current trends in nonconventional material removal processes," Ann. CIRP, vol. 35(2), p. 467 480, 1986.
[2] E. C. Jameson, Electrical Discharge Machining. Dearborn, Michigan: SME, 2001.
[3] O. H. Erzurumlu, T., "Comparison of response surface model with neural network in determining the surface quality of moulded parts," Materials and Design, vol. 28, no. 2, pp. 459-465, 2007.
[4] K. Wang, H. L. Gelgele, Y. Wang, Q. Yuan, and M. Fang, "A hybrid intelligent method for modelling the edm process," International Journal of Machine Tools and Manufacture, vol. 43, pp. 995-999, Aug 2003.
[5] M. K. Pradhan and C. K. Biswas, "Neuro-fuzzy model on material removal rate in electrical discharge machining in AISI D2 steel," Proceedings of the 2nd International and 23rd All India Manufacturing Technology, Design and Research Conference, vol. 1, pp. 469-474, 2008.
[6] M. K. Pradhan, R. Das, and C. K. Biswas, "Comparisons of neural network models on surface roughness in electrical discharge machining," Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 223, p. (In Press), 2009.
[7] D. Kanagarajan, R. Karthikeyan, K. Palanikumar, and P. Sivaraj, "Influence of process parameters on electric discharge machining of WC/30%Co composites," Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 222, no. 7, pp. 807-815, 2008.
[8] A. Jaharah, C. Liang, A. Wahid, S.Z., M. Rahman, and C. Che Hassan, "Performance of copper electrode in electical discharge machining (edm) of aisi h13 harden steel," International Journal of Mechanical and Materials Engineering, vol. 3, no. 1, pp. 25-29, 2008.
[9] P. Kuppan, A. Rajadurai, and S. Narayanan, "Influence of EDM process parameters in deep hole drilling of inconel 718," International Journal of Advance Manufacturing Technology, vol. 38, pp. 74-84, 2007. V (Volt) Toff (╬╝s) 40 42 44 46 48 50 100 90 80 70 60 50 Ra 2.6 - 3.0 3.0 - 3.4 3.4 - 3.8 3.8 - 4.2 4.2 - 4.6 < 4.6 - 5.0 5.0 - 5.4 > 5.4 2.2 2.2 - 2.6 Fig. 8. Effect of Toff & V on SR
[10] K. Chiang, "Modeling and analysis of the effects of machining parameters on the performance characteristics in the edm process of al2o 3+tic mixed ceramic," International Journal of Advanced Manufacturing Technology, vol. 37, no. 5-6, pp. 523-533, 2008.
[11] I. Puertas, C. J. Luis, and L. Alvarez, "Analysis of the influence of edm parameters on surface quality, mrr and ew of wc-co," Journal of Materials Processing Technology, vol. 153-154, no. 1-3, pp. 1026-1032, 2004.
[12] J. Rebelo, A. MorA˜ o Dias, R. Mesquita, P. Vassalo, and M. Santos, "Experimental study on electro-discharge machining and polishing of high strength copper-beryllium alloys," vol. 103, no. 3, pp. 389-397, 2000.
[13] K.-M. Tsai and P.-J. Wang, "Predictions on surface finish in electrical discharge machining based upon neural network models," International Journal of Machine Tools and Manufacture, vol. 41, pp. 1385-1403, Aug 2001.
[14] G. Petropoulos, N. Vaxevanidis, and C. Pandazaras, "Modeling of surface finish in electro-discharge machining based upon statistical multi-parameter analysis," vol. 155-156, no. 1-3, pp. 1247-1251, 2004.
[15] M. K. Pradhan and C. K. Biswas, "Investigations into the effect of process parameters on MRR in EDM of AISI d2 steel by response surface methodology," Journal of Mechatronics and Intelligent Manufacturing (JoMIM),Nova Science Publishers, USA., vol. (Accepted), 2009.
[16] D. C. Montgomery, "Design and analysis of experiments," John willy and Sons Inc., 2001.
[17] R. L. Mason, R. F., D. Gunst, Texas, and J. L. Hess., Statistical Design and Analysis of Experiments With Applications to Engineering and Science. 2nd Edition, A John Wiley & sons publication,, 2003.
[18] Minitab14, Minitab User Manual Release 14 MINITAB Inc,, State College, PA, USA,, 2003.