Experimental Study and Optimization of Electrochemical Machining of Al‐7Si‐0.4Mg Alloy Using NaNO ₃ and NaOH Electrolytes

This study focused on the electrochemical machining (ECM) of Al‐7Si‐0.4Mg alloy using a mixture electrolyte of NaNO 3 and NaOH. Experiments were designed based on the Taguchi method, utilizing an L16 orthogonal array, and input parameters such as voltage (V), electrolyte concentration (E), feed rate (F) and duty cycle (D) were varied to evaluate the effects on material removal rate (MRR) and surface roughness (SR). Residual analysis, ANOVA and signal‐to‐noise (SN) ratio analysis were conducted to determine the optimal settings for single‐response optimization. For multi‐response optimization, a hybrid statistical approach combining Taguchi and TOPSIS was employed. The Taguchi–TOPSIS combination analysis identified the optimal parameter combination as V4–E3–F2–D3, corresponding to a voltage of 14 V, an electrolyte concentration of 80 g/L, a feed rate of 0.5 mm/min and a duty cycle of 75%, which achieved the highest MRR and lowest SR. ANOVA results revealed that voltage is the most influential factor, contributing 91.3% to MRR and 60.6% for SR. Validation tests under these optimal conditions (V4–E3–F2–D3) yielded an MRR of 33.25 mm 3 /min and a SR of 0.164 μm. Compared to prior experimental results, the optimized parameters achieved through the Taguchi–TOPSIS approach led to a 7.32% increase in MRR and an 11.35% reduction in SR, confirming the reliability and effectiveness of this hybrid method in significantly improving machining performance. Finally, the integration of the hybrid statistical optimization strategy with the dual‐electrolyte formulation made a significant advancement in the ECM of Al alloys, providing a highly efficient and minimal surface damage.