Optimization of process parameters for machining of AISI-1045 steel using Taguchi design and ANOVA

Abstract Previous published works on the optimization of parameters in orthogonal cutting process have used a single tool. The parameters considered in these works are: surface roughness, power consumption, deformed chip shape, and temperature in the workpiece. This paper is on the optimization of machining parameters with multiple cutting tools. This is required to reduce the cutting forces and temperature while machining AISI 1045 steel. In this study, this has been achieved by using a combination of statistical tools including Taguchi matrix, signal to noise ratio, and analysis of variance (ANOVA). The effects of varying cutting speed, feed rate, depth of cut, and rake angle in orthogonal cutting process have been considered. The Finite Element (FE) simulations have been carried out with a general purpose commercial FE code, ABAQUS, and statistical calculations have been performed with Minitab. Results show that for optimum cutting forces, feed rate and depth of cut are the most important factors while for lower temperatures, cutting speed and rake angle play a significant role. It is concluded that carbide cutting tools is a better option as compared to uncoated cemented carbide cutting tool for machining AISI 1045 steel as it results in lower cutting forces and temperatures.