A novel approach of RSM-based TOPSIS-JAYA algorithm for optimization of ECM process parameters

Abstract

ABSTRACT Optimization of parameters of electrochemical machining (ECM) has attracted attention of many researchers of late, for making use of the full capability of the machine and in that process, material removal rate (MRR), over cut diameter (OC-Diameter), and over cut depth (OC-Depth) can be improved. With this objective, in this work, ECM set up has been made, experiments are conducted systematically, and process parameters are optimized by applying hybrid Technique of Order Preference by Similarity to the Ideal Solution-JAYA algorithm. Response surface methodology (RSM) based experimental design is considered with AISI P20+Ni steel as anode, tungsten wire as cathode, and NaCl as electrolyte. Regression models developed from RSM are validated successfully by conducting additional set of experiments and predictive values are compared with actual results. MATLAB code is prepared to determine optimum combination of machining process parameters applying TOPSIS-JAYA algorithm in multi-objective optimization context. Results indicated that optimum values are obtained for higher values of voltage, feed, electrolyte concentration, and lower value of tool diameter. The weights of MRR, OC-Depth, and OC-Diameter are varied in TOPSIS and sensitivity analysis is carried out.