APPLICATION OF GENETIC ALGORITHMS FOR MODELLING THE EDM PARAMETERS ON MACHINING OF AISI 4340 STEEL

Every production /manufacturing unit mainly focuses on Productivity and quality which are two important aspects and have become great concerns in today's competitive global market. In the present work, maximizing the Material Removal Rate (MRR) as productivity estimate and minimizing Surface Roughness (SR) is taken as most important output for the Electrical discharge machining (EDM) process. EDM is still an experience process and at the same time selecting optimization and modeling parameters is costly and time consuming. With an intention of these two opposite in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis (RA) and Analysis of Variance (ANOVA) and is optimized using Genetic Algorithm (GA) technique. The model is shown to be effective MRR and SR improved using optimized machining parameters. The material used for the machining is AISI 4340 steel and the electrode material is copper.