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This study optimizes the electrical discharge machining (EDM) process for Ti-6Al-4 V alloy using Response Surface Methodology (RSM) and Grey Relational Analysis (GRA). Input parameterspeak current, pulse-on time (Ton), and pulse-off time (Toff)were varied to enhance Material Removal Rate (MRR) and Surface Roughness (SR). Experiments utilized a tungsten carbide electrode and kerosene as the dielectric fluid. Results indicated peak current significantly influences MRR and SR. The highest MRR of 8.52 mm³/min was achieved at 22 A, while the lowest SR of 2.65 µm occurred at 12 A. ANOVA confirmed the peak current ( P = 0.000) and Toff ( P = 0.016) significantly affect MRR, with an R² value of 98.9 %, validating model reliability. Multi-objective optimization identified ideal settings for maximizing MRR and minimizing SR, further validated by confirmation experiments. The integrated RSM-GRA approach proved effective for EDM performance improvement.
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Mohankumar et al. (2025) studied this question.
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