Grey Relational Parameter Optimization in Ultrasonic Machining of Ceramic Composite (Al2O3/Zro2)

In this paper, the multi-objective optimization is used to measure the performance of ultrasonic machining of ceramic composite using grey relational theory. The measures of performance chosen were material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). Initially the optimal process parameters for individual responses were determined using parameter design proposed by the full factorial design of experiment. Later, a grey relational grade obtained from the grey relational analysis is used to compare the above performance measures. Experimental results show that when process parameters were set as amplitude of 70% and slurry concentration of 10% with pure black SiC slurry, the ultrasonic machining produces higher material removal rate with lower tool wear rate associated with high surface finish.