Optimization of EDM process parameters using MCDM based on customer preference rating method

Abstract

Nowadays, multi-objective optimization tools have been used in manufacturing processes to decide the optimal process parameters. Optimization method with a more advanced tool is required to obtain the finest EDM process parameters such as peak current, voltage, pulse on duration, pulse off duration, pressure. This research work utilizes the Multi-Criteria Decision Making Method (MCDM) for identifying the optimal process parameters according to customer preference rating method (CPR). CPR draws a weightage to the output responses of the machine and characteristics of the machined surface as per customer requirement. Genetic Algorithm (GA) and TOPSIS are extensively involved in solving multi-objective optimization problems. Optimization of process parameters were determined using Genetic Algorithm (GA) integrated with TOPSIS to achieve higher Metal Removal Rate, Micro Hardness, low surface roughness, tool wear rate and actual depth. There are fifty Pareto-optimal solutions performed and the best solution has been selected based on rank. The optimal solution of the GA was given to the TOPSIS as input for further improvement. The optimal value obtained through GA has been enhanced with TOPSIS.