Multi-response optimization and analysis of Al/B4Cp EDM using grey relational analysis / Mangesh Phate, Shraddha Toney and Vikas Phate

Development of material, especially metal matrix composite (aluminum-based MMC), attracts worldwide researchers due to its enhancement in wear and abrasive resistance, lightweight and high strength, low coefficient of thermal expansion. This work investigates the electrical discharge machining (EDM) of Aluminum/Boron Carbide (Al/B4C) MMC. The optimization will help the researchers or metal processing industries use the investigated optimized process parameters for efficient and effective machining parameters. Pulse on time (PON), pulse off time (POFF), a variation of boron carbide(CP), and input current (IP) were varied to measure material removal rate (MRR), wear rate of the tool (TWR), and the surface roughness (Ra). The Taguchi method is used for the analysis of the machining parameters. Grey relational grade (GRA) is employed for the optimization of machining responses and the input parameters. The influence of various EDM parameters is investigated by analysis of variance (ANOVA). The multi-response optimization was carried out by GRA (CP: 4% of B4C, PON” 25 micro-sec, POFF: 9 micro-sec, and input current of 8 amp). The optimum responses were MRR: 17.58 mm3/sec, TWR: 0.064 mm3/sec, and Ra: 1.20 microns. The Aluminum-based alloys or composites are widely used in aerospace applications, automobile sectors, construction, aircraft industries, etc.