Statistical analysis of surface roughness using RSM in hard turning of AISI 4340 steel with ceramic tool

Abstract

The present study concerns the modeling and optimization of surface roughness in dry hard turning of high-strength low-alloy (HSLA) grade AISI 4340 steel (49 HRC) with coated ceramic tool. For parametric study, the turning operations have been established according to Taguchi L27 orthogonal array consisting of an experimental design matrix 3 levels and 3 principal turning parameters (factors) such as, cutting speed, axial feed, and depth of cut. Analysis of sixteen set experimental data with ANOVA showed that axial feed and speed are the most significant controlled cutting parameters for hard turning operation, if the improvement of the machined surface finish is considered. Thereafter, statistical regression model based on response surface methodology has been proposed for correlation of cutting parameters with machined workpiece surface roughness. Finally, optimal cutting conditions with the aim to minimize the surface roughness via desirability function approach of RSM are proposed.