Optimization of process conditions of Powder Mixed Electric Discharge Machining of Nickel based Superalloy using Grey Wolf Optimizer algorithm

Abstract

The Powder-Mixed Electric Discharge Machining (PMEDM) process has been drawing the attention of researchers since it could successfully overcome some of the limitations of the conventional Electric Discharge Machining (EDM) process. There was extensive research carried out on the PMEDM process to explore various possibilities for enhancing the process output. In the present work, an experimental study has been undertaken to investigate the influence of three conductive powders: zinc, cobalt, and molybdenum, while machining Nimonic 75, a nickel-based superalloy, by the EDM process. The work material considered in the study has been widely used in the aerospace industries and in applications involving higher temperatures. The experiments were carried out based on the Response Surface Methodology using the Box–Behnken design. Using the experimental data, regression equations were formed to predict the outcome of the process, which are Material Removal Rate (MRR), Electrode Wear Ratio (EWR), and Surface Roughness (SR). This work attempted to optimize the EDM machining parameters using the Grey Wolf Optimizer (GWO) algorithm combined with the Utility concept. The optimum conditions obtained by the GWO algorithm were: Powder – Molybdenum; Concentration of powder – 5.4 g/L; Discharge current – 4 A; Duty factor – 0.8.