Multi-Response Optimization of EDM Parameters for Nano-ZrO? Reinforced Aluminum Matrix Composites Using Taguchi–Grey Relational Analysis

This study investigates the elaboration of aluminum matrix composites reinforced with nano-sized zirconium dioxide (ZrO₂) particles (25 ± 5 nm) fabricated via the stir casting technique and evaluates their machinability using Electric Discharge Machining (EDM). The Taguchi method, based on an L9 orthogonal array, was employed to analyze and optimize the EDM process by examining the effect of three process parameters: peak intensity (IP), pulse-on time (TON), and pulse-off time (TOFF), each at three levels. Material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra) were selected as the primary performance responses. Signal-to-noise (S/N) ratio analysis was applied using the “Larger-is-Better” criterion for MRR and the “Smaller-is-Better” criterion for TWR and Ra. To obtain a single optimal machining condition considering all responses simultaneously, Grey Relational Analysis (GRA) was employed. The results indicate that peak intensity is the most influential parameter affecting all output responses, particularly MRR. The combined Taguchi–GRA approach identified the optimal EDM parameters as IP = 14 A, TON = 60 μs, and TOFF = 20 μs, yielding improved machining efficiency with reduced tool wear and acceptable surface quality. The findings demonstrate that nano-ZrO₂ reinforcement significantly enhances the EDM machinability of aluminum-based composites. These results are of practical relevance for industrial applications requiring high machining efficiency and reliable surface integrity, particularly in marine, structural, and corrosion resistant components.