An intelligent approach to optimize the electrical discharge machining of titanium alloy by simple optimization algorithm

Abstract

Electrical discharge machining (EDM) is a thermo-electrical process that can be conveniently utilized for generating complex shaped profiles on hard-to-machine conductive materials using metallic tool electrodes. In this work, composite tools made of copper-tungsten-boron carbide (Cu-W-B4C) manufactured by powder metallurgy (PM) route are used during machining of titanium alloy (Ti6Al4V). The effect of four input machining parameters viz. current, pulse-on-time, duty cycle and percentage of tungsten and boron carbide on material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) is studied. A novel meta-heuristic approach such as simple optimization (SOPT) algorithm has been used for single and multi-objective optimization. The pareto-optimal solutions obtained by SOPT have been ranked by VIKOR method to find out the best suitable optimal solution. Analysis of experimental data suggests vital information for controlling the machining parameters to improve the machining performance.