Modeling and Optimization of MRR in Wire Electrical Discharge Machining of Silicon Particle-Reinforced AA6063 Composite

Abstract

Improved properties can be found in aluminum alloys containing silicon carbide reinforcement particles. This work studies the machinability of Al 6063 reinforced with silicon carbide particles with wire electrical discharge machining. To attain a high material removal rate, wire EDM constraints such as current (I), pulse-on time (Ton), wire speed (Ws), voltage $\left(I_v\right)$ , and pulse-off time (Toff) can be adjusted with precision. Taguchi L16 orthogonal arrays are used to design the experiments and statistical methods are used to examine. These process characteristics had a significant impact on the overall rate of return, with a 28.2% impact on the MRR, 23.04% impact on the MRR, and 22.86% impact on the MRR. We achieved MRRs of 65.21 mg/min for samples containing 5% and 10% SiCp at optimal conditions, respectively. Linear regression was used to create the statistical model, which then used confirmation trials to verify its accuracy in predicting MRR (R -73.65%). The statistical model is used to estimate MRR based on various process parameter settings.