Optimization of EDM input variables for machining of novel Al7010/B4C/BN hybrid metal matrix nanocomposite using multi objective grey relational analysis

Abstract

In this research, the examination on the influence of EDM pulse variables during machining of Al7010/B₄C/BN hybrid metal matrix nanocomposites (HMMNCs) manufactured by using ultrasonic assisted stir casting (UASC) route. The optimum input factors of die sinking EDM like pulse on time (Pon), discharge current (DC), gap voltage (GV) and pulse off time (Poff) on performance factors like tool wear rate (TWR), material removal rate (MRR), and surface roughness (SR) were studied. The Taguchi experimental design of L₁₆ orthogonal array (OA) was selected for conducting experiments. The ANOVA route was utilized to obtain the % contribution of pulse parameters on response factors. The multi objective Grey relational analysis (GRA) was used for determining optimum machining condition. The results indicated that discharge current was more effects on output factors like SR, TWR and MRR followed by other parameters and that DC is the best substantial factor for multiple objective responses. The results exposed that the optimum EDM process factors condition is A₁B₁C₁D₃. The outcomes were further calculated by employing confirmatory experiment. Scanning electron microscope (SEM) was conducted to observe the surface properties of a specimen that underwent EDM. In the EDMed surface a complex combination surrounded by tiny and big melt droplets, various-sized fissures, microcracks, and void markings were presented. Moreover, observed the effects on the surface, such as the formation of a recast layer.