Multi-criteria data-driven optimization of µ-ECM performance in zirconia strengthened Al7050 (Al-Zn-Mg-Cu) alloy composite using an integrated Taguchi-TOPSIS approach

Zirconia-reinforced aluminum matrix composites are increasingly explored for aerospace and precision engineering applications due to their high strength, lightweight nature, and improved wear resistance. However, conventional machining of these composites is often associated with severe tool wear, burr formation, and dimensional inaccuracies arising from the presence of hard ceramic reinforcements. This study investigates the micro-electrochemical machining (µ-ECM) performance of a stir-cast Al7050 (Al–Zn–Mg–Cu) alloy reinforced with 12 wt.% ZrO 2 particles using an integrated Taguchi-TOPSIS optimization approach. Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) confirmed the successful incorporation and relatively uniform distribution of ZrO 2 particles within the matrix. µ-ECM experiments were designed using Taguchi’s L9 orthogonal array by varying current (I), voltage (V), and electrolyte concentration (C), while material removal rate (MRR) and overcut (OC) were selected as performance responses. The results revealed that increasing current enhanced electrochemical dissolution and significantly improved MRR, although it also influenced OC formation. Multi-response optimization using TOPSIS identified the optimum machining condition as 2.0 amps, 30 V, and 10 g/L electrolyte concentration. Minimum OC was observed at 1.0 amps, 10 V, and 30 g/L. ANOVA showed that current was the dominant factor affecting both MRR and OC, accounting for 77.31% and 85.45%, respectively. Confirmation experiments produced a minimum prediction error of 0.55%.