Improving Surface Quality in CNC Turning of AISI 1045 Steel through Taguchi-Based Process Optimization

Abstract

Surface roughness is an important aspect of machining quality that affects the performance, life, and functional efficiency of components. This research focuses on improving the surface finish of AISI 1045 steel using CNC turning, through systematic optimization of cutting parameters based on the Taguchi methodology. Three major process parameters cutting speed, feed rate, and depth of cut were studied at three different levels using an L9 orthogonal array. Machining experiments were performed with carbide inserts under wet conditions. The results were analysed using signal-to-noise. S/N ratio and ANOVA were performed to calculate the significance of each parameter. The study discovered that feed rate had the most significant influence on surface roughness, while cutting speed and the depth of cut contributed comparatively less. Confirmation tests validated the predicted optimal settings, showing that the Taguchi approach is an efficient and reliable method to improve surface quality in CNC turning.