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K. Dev, A. Pratap, S. Agarwal and T. Meyarivan, “A Fast and Elitist Multi Objective Genetic Algorithm: NSGA-II,” IEEE Transactions on Evolutionary Compu- tation, Vol. 6. No. 2, 2002, pp. 182-197. doi:10.1109/4235.996017

has been cited by the following article:

• TITLE: Optimization of ECM Process Parameters Using NSGA-II

  AUTHORS: Chinnamuthu Senthilkumar, Gowrishankar Ganesan, Ramanujam Karthikeyan

  KEYWORDS: Electro Chemical Machining; Metal Removal Rate; Response Surface Methodology; Surface Roughness; NSGA-II

  JOURNAL NAME: Journal of Minerals and Materials Characterization and Engineering, Vol.11 No.10, October 31, 2012

  ABSTRACT: Electrochemical machining (ECM) could be used as one of the best non-traditional machining technique for machining electrically conducting, tough and difficult to machine material with appropriate machining parameters combination. This paper attempts to establish a comprehensive mathematical model for correlating the interactive and higher-order influences of various machining parameters on the predominant machining criteria, i.e. metal removal rate and surface roughness through response surface methodology (RSM). The adequacy of the developed mathematical models has also been tested by the analysis of variance (ANOVA) test. The process parameters are optimized through Nondominated Sorting Genetic Algorithm-II (NSGA-II) approach to maximize metal removal rate and minimize surface roughness. A non-dominated solution set has been obtained and reported.