Multi-objective Optimization of Electro-chemical Machining by Non-dominated Sorting Genetic Algorithm☆

Quality of machined surface strongly depend on the selection of optimal parameter settings and type of machining process. Electro-chemical machining (ECM) offers several unique feature, like higher machining rate, better surface finish, and it is suitable for machining a wide range of materials. In this regard, an attempt has been made to develop a mathematical model for responses i.e. metal removal rate (MRR) and surface roughness (SR) through regression analysis for electro-chemical machining on EN 19. And analysis of variance (ANOVA) test is perform to check the aptness of the developed mathematical models. The performance for ECM process is optimized through Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for maximizing the metal removal rate and minimizing the surface roughness. Through this non-dominated optimum parameter settings has been obtained and reported.

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