Parameter optimization of wire electric discharge machining process using GA and PSO

Wire Electric Discharge Machining (WEDM) is one of the important non-traditional machining processes for machining of intricate profiles in conductive and difficult to machine materials. The machining performance of this process largely depends on various process parameters, such as applied voltage, ignition pulse current, pulse-off time, pulse duration, serve controlled reference mean voltage, servo-speed variation, wire speed, wire tension and injection pressure. As WEDM is a complex process, it is difficult to determine optimal parameters for improving cutting performance, which is cutting velocity and surface finish. It is important to note that it is not possible to have a unique set of optimal combination of cutting parameters as the influence of the above cutting parameters on both the responses are opposite to each other. The present paper deals with the multi-objective optimization of WEDM process using evolutionary algorithms, such as non-dominated sorted genetic algorithm and Practical Swarm Optimization. As the WEDM process contains two objectives, a multi-objective optimization criterion is used.