Machining magnesium alloys using traditional methods pose several challenges which includes high flammability, accelerating wear, high material degradation, oxidation, and poor surface finish under machining forces. These challenges are overcome with non contact substrate type of wire electrical discharge machining (WEDM). This study carried out WEDM of AZ91D magnesium alloy by conducting various experiments based on Taguchi L18 orthogonal array. The key attributes which influence WEDM such as wire feed rate (WF), fluid pressure (FP), gap voltage (GV), pulse on period (PTON), and pulse off period (PTOFF) were utilized to assess the quality characteristics like surface irregularity (Ra), material removal rate (MRR), and microhardness (MH). Additionally, a hybrid method combining gray relational analysis (GRA) with genetic algorithm (GA) were developed and applied to achieve multi objective optimization of quality characteristics. The effects of key attributes on the quality characteristics have been studied. The percentage improvement between the hybrid GRA-GA and GRA approach contributed 33.552% for MRR, 20.8619% for Ra, and 8.34% for MH. The percentage error difference between the expected and experimental values varies within the range of ±5%, which implies strong correlation. The optimal setting were fluid pressure:- 1 bar; pulse-on-period:- 125 µs; pulse-off period:- 60 µs; gap voltage:- 10 V; wire feed rate:- 4 mm/min for minimum material removal rate and surface irregularity and for maximum microhardness. The optimized parameters can enhance the accuracy and quality of machining for medical implants, leading to improved biocompatibility and reduced risk of complications.
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