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Modeling and Optimization of Process Parameters in PMEDM by Genetic Algorithm

Authors: Farhad Kolahan, Mohammad Bironro


This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.

Keywords: Optimization, GeneticAlgorithm, Regression modeling, PMEDM

Digital Object Identifier (DOI):

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[1] H. Zarepour, A.F. Tehrani, D. Karimi, and S. Amini, "Statistical analysis on electrode wear in EDM of tool steel DIN 1.2714 used in forging dies," J. Mater Process Tech., vol. 188, pp. 711-714, 2007.
[2] A.Ghosh, A.K. Mallik, Manufacturing Science, Affiliated East-West Press, New Delhi, 1991.
[3] B.H. Yan, H.C. Tsai, F.Y. "Huang, The effect of EDM of a dielectric of a urea solution in water on modifying the surface of titanium". Int. J. Mach. Manuf., vol. 45, no. 2, pp. 194-200, 2005.
[4] K.H. Ho, S.T. Newman, "State of art electrical discharge machining (EDM)", Int. J. Mach. Manuf. Vol. 43, no 13,pp 1287-1300, 2003.
[5] Puertas, C.J. Luis, "A study on the machining parameters optimization of electrical discharge machining", J. Mater. Process Tech , vol. 144, pp. 521-526, 2003.
[6] M.M. Schwartz, Engineering applications of ceramic materials, American Society for Metals, Metals Park, Ohio. 1995.
[7] F.K. locke, "Modern approaches for the production of ceramic components", J. Eur. Ceram. Soc., vol. 17, pp. 457-465, 1997.
[8] J.T. Huang and Y.S. Liao, "Optimization of machining parameters of wire-EDM based on grey relational and statistical analysis", Int. J. Prodn. Res. vol. 41, no. 8, pp. 1707-1720, 2003.
[9] K.Y. Kung, J.T. Horng, and K.T. Chiang, "Material removal rate and electrode wear ratio study on the powder mixed electrical discharge machining of cobalt-bonded tungsten carbide", Int. J. Adv Manuf. Technol., to be published.
[10] D.C. Montgomery, E.A. Peck, G.G. Vining, Introduction to Linear Regression Analysis, Third ed., Wiley, New York, 2003.
[11] G.R. Cheng, Genetic algorithm and engineering design, New York: John Wiley & Sons, 1997.
[12] J.C. Su , J.Y. Kao, and Y.S. Tarng, "Optimization of the electrical discharge machining process using a GA-based neural network". Int. J. Adv. Manuf. Tech., vol. 24, pp 81-90, 2004.