Effect of Machining Parameters and Optimization of Machining Time in Facing Operation using Response Surface Methodology and Genetic Algorithm

Abstract

Optimum selection of machining parameters and its cutting conditions plays a major role in increase of productivity and minimization of total machining time. A significant improvement in process may lead to increase the process efficiency and low cost of manufacturing. In this research, Spindle speed, Feed rate, Depth of cut and End relief angle is considered as an input parameter for facing the A22E Bimetal bearing material using M42 HSS tool material. A second order mathematical model is developed using Design of Experiments (DoE) of Response Surface Methodology (RSM) to predict machining time on bimetal bearing material using special Industrial type of CNC lathe. The Analysis of Variance (ANOVA) was used to study the performance characteristics in facing operation. The values of Prob>F less than 0.05 indicate model terms are significant. Design Expert software is used to analyze the direct and interaction effects of the machining parameter. The genetic algorithm (GA) is trained and tested using MATLAB 7.0. The GA recommends 1.169 seconds as the best minimum predicted machining time value. The confirmatory test shows the second order regression predicted values and experimental values were very close and good agreement.