36 X INDIAN JOURNAL OF APPLIED RESEARCH

In this article a optimization technique is proposed for optimizing the responses such as surface roughness and cutting force in turning of nano alumina particulate reinforced LM25 aluminum alloy metal matrix composites. The optimum machining parameters selection is a very important task to the process planer to achieve desired surface roughness with minimum machining cost. In this study, the optimization effect of machining parameters on surface roughness and cutting force in finish turning operation was investigated by using the Taguchi method. The experimental studies were conducted under simultaneously varying cutting speed, feed, and depth of cut. An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) were employed to study the performance characteristics in the turning of LM25 aluminum alloy metal matrix composites using uncoated cemented carbide cutting tool inserts. The optimum machining parameters are experimentally validated for minimization of surface roughness and minimization of cutting force. Introduction and surface finish may be two important responses that need to be monitored in the finishing operation. Cutting speed, feed and depth of cut are the three independent parameters tha