Selection of EDM Process Parameters Using Biogeography-Based Optimization Algorithm

Abstract

Amongst the nontraditional machining processes, electric discharge machining (EDM) is considered to be one of the most important processes for machining intricate and complex shapes in various electrically conductive materials, including high-strength, temperature-resistant (HSTR) alloys, especially in aeronautical and automotive industries. For achieving the best performance of the EDM process, it is imperative to carry out parametric design which involves characterization of multiple process responses, such as material removal rate, tool wear rate, surface finish and surface integrity, heat affected zone, etc., with respect to different machining parameters, like peak current, pulse-on time, duty factor, gap voltage, and dielectric flushing pressure, followed by parametric optimization of the process. This article focuses on the application of the biogeography-based optimization (BBO) algorithm for single and multiobjective optimization of the responses of two EDM processes. The optimization performance of the BBO algorithm is compared with that of other population-based algorithms, e.g., genetic algorithm (GA), ant colony optimization (ACO), and artificial bee colony (ABC) algorithm. It is observed that the BBO algorithm performs better than the others with respect to the optimal process response values.