Modelling And Optimization Of Alumina & Silica Reinforced Magnesium Metal Matrix Composite Using RSM BBD Approach & ANOVA For Quantitative Parameters

Abstract

This paper explains the optimization of quantitative parameters for thermoelectric machining of magnesium based metal matrix composite. Sample prepared by stir casting method using Al₂O_3p (3%wt) and SiC_p (6%wt) as reinforcement. CNC wire cut EDM used for machining as per DoE developed using RSM-BBD approach. Input parameters Pulse on, pulse off time, current and wire speed was varied to obtain machining efficiency and surface quality. Experimental models are developed and justified by ANOVA for optimization and response plots depicting optimized parameters of higher metal removal rate and lower roughness. Current and wire speed played significant role in obtaining the optimum values of input parameters. Higher value of MRR is obtained at T_on=18µs, T_off=7µs, I=1A & WS=10.40m/sec while lower value of roughness is obtained at T_on=6µs, T_off=7µs, I=1A & WS=6.76m/sec. DoE based RSM-CD approach for multi objective optimization depicts combination of optimal input parameters T_on=6µs, T_off=5µs, I=1.2A & WS=10.4m/sec for high MRR (0.153128 mm³/sec) and lower surface roughness (Ra=2.98165µm).