Multi-Objective Optimization of EDM Process Parameters in Machining SAE 1015 Mild Steel: A Taguchi-DOE Approach

Abstract

Electrical discharge machining (EDM) can cut any electrically conductive material regardless of its hardness, but low-carbon steels such as SAE 1015 have seldom been examined in a systematic way. Here, the influence of source voltage (A), discharge current (B), pulse-on time (C) and pulse-off time (D) on material removal rate (MRR) and surface roughness (Ra) is investigated for die-sinking EDM of SAE 1015 mild steel with a graphite electrode. Experiments followed a nine-run Taguchi-based plan, and the data were processed in Minitab 17 through signal-to-noise (S/N) ratios, analysis of variance (ANOVA) and linear regression. Discharge current emerged as the dominant factor for both responses. For surface roughness it was the only statistically significant factor (p = 0.017; 39.7% of total variation). The regression model returned R2 = 89.9% and adjusted R2 = 79.9%, yet its leave-one-out predicted R2 was negative, so the model should be read as descriptive and not predictive. The best S/N settings for MRR (A2B3C2D2) and for roughness (A1B1C1D3) disagree, which is why a grey relational multi-objective analysis was applied. The response optimizer put the maximum predicted MRR at 58.68 mm3/min for 200 V, 48 A, 6.4 µs and 12.8 µs.