TY - JFULL AU - Farhad Kolahan and Mohammad Bironro PY - 2008/1/ TI - Modeling and Optimization of Process Parameters in PMEDM by Genetic Algorithm T2 - International Journal of Mechanical and Mechatronics Engineering SP - 1318 EP - 1323 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/6061 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 24, 2008 N2 - 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. ER -