The use of Taguchi method with grey relational analysis to optimize the EDM process parameters with multiple quality characteristics

Multi-criteria optimization of processes parameters could be used to simultaneously achieve several conicting goals such as increasing product quality and reducing production time. in this paper, grey relational analysis (gra) and taguchi method have been employed to optimize electrical discharge machining (edm) process parameters for aisi 2312 (40crmnmos86) hot worked steel alloy. the experimental data are gathered based on taguchi l36 design matrix. the tests are conducted under varying peak current (i), voltage (v ), pulse on time (ton), pulse off time (toff) and duty factor (η). the process output characteristics include surface roughness (sr), tool wear rate (twr) and material removal rate (mrr). the objective is to find a combination of process parameters to minimize twr and sr and maximize mrr. the three performance characteristics are combined into a single objective using grey relational analysis. the gra was followed by the signal to noise ratio to specify the optimal levels of process parameters. the significance of the process parameters on the overall quality characteristics of the edm process was also evaluated quantitatively using the analysis of variance (anova) method. optimal results were verified through additional experiments.