Investigation and Multi-response Optimization of Process Parameters of Electrical Discharge Machining on H21 Steel Using GRA-TOPSISCRITIC Method

The efficiency of optimizing numerous response parameters of electrical discharge machining (EDM) is investigated in this study with the assistance of grey relational analysis (GRA) and the approach for the order of preference by similarity to the ideal solution (TOPSIS) coupled with the criteria importance through criteria inter-correlation (CRITIC) method. The study considered polarity, peak current, electrode material, pulse-on time $\left(T_{\text {on }}\right)$, pulse-off time $\left(T_{\text {off }}\right)$, electrode material, polarity, and dielectric as the machining process parameters (MPPs) while using material subtraction rate (MSR), surface roughness, and tool degradation rate (TGR) as response parameters. First, Taguchi’s L18-OA was used to execute the experiments, and the response parameters were then recorded. The analysis of variance (ANOVA) was carried out to determine the influential MPP with 95% confidence level. The findings indicate that the optimal parametric settings were $2 \mathrm{~A}$ peak current, $60 \mu \mathrm{s} \mathrm{T}_{\text {on }}, 60 \mu \mathrm{s} \mathrm{T}_{\text {off }}$, copper electrode material, reverse polarity, and distilled water dielectric using the GRA-CRITIC method, and $4 \mathrm{~A}$ peak current, $30 \mu \mathrm{s} \mathrm{T}_{\text {on }}, 20 \mu \mathrm{s} \mathrm{T}_{\text {off, brass electrode, }}$, reverse polarity, and kerosene dielectric using TOPSIS CRITIC. The Peak current was found to be the most influential MPP, contributing 25.19% to the performance measures, followed by $\mathbf{T}_{\text {on }}, \mathbf{T}_{\text {off }}$, electrode material, polarity, and dielectric, contributing $24.45 \%, 13.42 \% ; 13.04 \%, 9.45 \%$, and 6.23%, respectively. Furthermore, the ANOVA of preference values revealed that $T_{\text {off }}$ had the maximum influence on performance measures, contributing 24.55% of the performance measures, followed by peak current $(16.30 \%)$, polarity $(10.67 \%), \mathrm{T}_{\text {on }}(6.67 \%)$, electrode material $(4.57 \%)$, and dielectric fluid $(6.57 \%)$. Confirmatory tests were run on the derived optimal values, and the findings indicated that the final improvements in the preference and grey grade values were 0.008016 and 0.006728, respectively. In addition, regression analysis was performed to evaluate the relation among the machining variables.