Optimizing EDM process parameters with the use of GRA-based RSM for machining titanium alloy

• Developed a hybrid GRA-RSM methodology for multi-objective optimization of EDM parameters for machining titanium alloys. • Achieved significant improvements in surface roughness, material removal rate, and tool wear performance. • Identified optimal EDM parameter settings for enhanced machining efficiency and precision. • Demonstrated the applicability of GRA-RSM in addressing complex engineering optimization challenges. • Provided actionable insights for practitioners working with titanium alloys in advanced manufacturing processes. 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.