Optimization of Cutting Parameters on Carbon Steel Using Taguchi-Grey Relation Method

In machining process, surface roughness and material removal rate have a vital importance since they affect mass production, consumption of energy, force, and tool life and product quality. In this study, Taguchi-Grey Relation Method (TGRM) is applied to AISI 1040 mild steels in the hardened form when machined with ceramic inserts using response surface methodology for multi-objective optimization. Grey-Relation Method and Pareto chart reveal that feed rate, depth of cut, speed besides square effect of speed/feed rate are effective parameters on the response. Among all eighteen experiments, trial twelfth provides the best multi-performance characteristics while the first experiment shows the worst performance. Optimal levels are determined at higher speed, higher feed rate associated with higher depth of cut. It is concluded that quadratic regression model and reduced quadratic regression model are developed. The correlation coefficients range from 98.3% to 96.89%, respectively. As a result, TGRM has an efficient to provide a good modelling in combination of surface roughness and metal removal rate.