Multi-objective optimization in electrical discharge machining of SiC and/ or B4C reinforced Al7075 using grey relational analysis

A composite material is a material system made up of two or more materials (or phases of the same material) that are insoluble in one another. Their qualities are frequently in the middle of those of the matrix material and the reinforcements. The current study examines the machining behaviour of Al-7075 metal matrix composites (AMMCs) reinforced with (4.5 percent B4C and 4.5 percent SiC) produced by stir casting. In the literature on AMMC machining behaviour, the influence of electrical discharge machine (EDM) process parameters such as voltage (V), current (I), pulse-on time, and pulse-off time on performance characteristics was investigated. Material Removal rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (Ra) was investigated. The L18 orthogonal array design of experiments has been studied experimentally, and the optimal machining conditions for (Al7075-4.5 % B4C +4.5 % SiC) samples will be determined using Grey relational analysis (GRA) based on the Taguchi approach. The GRA findings show that the optimal process parameter combination is V 140 volts, Ip 10 A, Ton 50 seconds, and Toff 25 seconds. Through a response table, it was discovered that the voltage has a stronger impact than the rest of the input parameters in obtaining a higher material removal rate (MRR) and lower electrode wear rate (EWR) and surface roughness (Ra). The study discovered that by choosing the right process parameters, the multi-performance characteristic may be improved.