Multi-Responses Optimization Of Edm Sinking Process Of Aisi D2 Tool Steel Using Taguchi Grey–Fuzzy Method

Abstract

Rough machining with Electro Discharge Machining (EDM) process gives a large Material Removal Rate (MRR) and high Surface Roughness (SR), while finish machining gives low SR and very slow MRR. In this study, Taguchi method coupled with Grey Relational Analysis (GRA) and fuzzy logic has been applied for optimization of multiple performance characteristics. The EDM machining parameters (gap voltage, pulse current, on time and duty factor) are optimized with considerations of multiple performance characteristics, i.e., MRR and SR. The quality characteristic of MRR is larger-is-better, while the quality characteristic of SR is smaller-is-better. Based on Taguchi method, an L18 mixed-orthogonal array is selected for the experiments. By using the combination of GRA and fuzzy logic, the optimization of complicated multiple performance characteristics was transformed into the optimization of a single response performance index. The most significant machining parameters which affect the multiple performance characteristics were gapvoltage and pulse current. Experimental results have also shown that machining performance characteristics of EDM process can be improved effectively through the combination of Taguchi method, GRA and fuzzy logic.