Optimization of Material Removal Rate and Surface Roughness in EDM Machining of Metal Matrix Composite using Genetic Algorithm

Aluminium Silicon Carbide (AlSiC) is most widely used in the fields of aerospace, electronics, military, automobile and medical etc., in the form of dies, components, and products. The present work has been carried out to optimize the machining parameters on Electric Discharge Machine (EDM) using AlSiC as work piece and pure copper as electrode. Machining parameters which are investigated in this work are Material Removal Rate (MRR) and surface roughness. Control parameters used are discharge voltage (v), discharge current (Ip), Pulse duty factor (Tau), Pulse on time (Ton). Taguchi technique (L16b orthogonal array) was used for design of experiments and genetic algorithm for optimization. The analysis of material removal rate yields optimum values when current is high and voltage is low where as surface roughness is best when both are low. (c) 2017 Published by Elsevier Ltd.