Bi-performance optimization of electrochemical machining characteristics of Al/20%SiCp composites using NSGA-II

Abstract Electrochemical machining (ECM) is one of the important non-traditional machining processes, which is used for machining of difficult-to-cut materials and intricate shapes. Being a complex process, it is very difficult to determine optimal parameters for improving cutting performance. The cutting parameters used for the experiments were electrolyte concentration, electrolyte flowrate, applied voltage, and tool feed rate. Experiments were carried out according to response surface methodology (RSM). Statistical models based on second-order polynomial equations were developed for the different responses. The non-dominated sorting genetic algorithm (NSGA-II) tool was used to optimize the ECM process parameters to maximize MRR and minimize Ra. A non-dominated solution set has been obtained and reported.