Optimization of the milling parameters for an Al/Si3N4 functionally graded composite using grey relational analysis

Abstract

Abstract This study involves the multi-objective optimization of end milling process parameters during machining of Al-Si5Cu3/Si3N4 functionally graded metal matrix composite that was fabricated using centrifugal casting route. The dimension of the cast sample was 150 × 150 × 20 mm3. The hardness of the sample was measured along the radial direction. It was found that the hardness at the outer periphery was greater than that of other points along the radial direction. Therefore, the machining experiment was carried out only at the outer periphery. Taguchi's design of experiments method was employed and sixteen levels of experiments were conducted by varying the input parameters namely the cutting speed (355, 500, 710 and 1000 rpm), the depth of cut (0.5, 0.9, 1.2 and 1.5 mm) and the feed rate (250, 315, 400 and 500 mm × min−1). Multi-objective optimization using grey relational analysis was performed and the optimal set of input parameters were found to be cutting speed of 1000 rpm, feed rate of 250 mm × min−1 and depth of cut of 1.5 mm. Using analysis of variance technique, it was found that cutting speed, depth of cut and feed rate have an influence of 63.57, 16.83 and 8 %, respectively, on the optimal solution.