Optimization of relative wear ratio during EDM of titanium alloy using advanced techniques

Abstract

This study presents the relative wear ratio (RWR) optimization of Titanium alloy 685 for electric discharge machining (EDM). Titanium alloys are widely used in modern industry due to its excellent engineering property like high strength to weight ratio, corrosion resistance. There is difficulty in the machining of titanium alloy with conventional machining processes, hence EDM used to machine titanium alloy. The objective is to maximize the material removal rate (MRR) while the tool wear rate (TWR) should be minimized. The machined surface is an exact replica of the tool face. If TWR increases then the quality of the machined surface deteriorate. A new term introduces a RWR which represents the ratio of MRR to the TWR. The high value of RWR is desired to improve the quality of the machined surface. In this paper RWR is optimized. Response surface model used to develop a regression model of RWR. Optimization of RWR is done by advanced optimization techniques, Jaya Algorithm, teaching-learning-based optimization and response optimizer. Parameters optimization of peak current (Ip), pulse on time (Ton), duty factor (t) and voltage (V) done in this study to maximize RWR.