Regression modeling and comparative analysis on CNC wet-turning of AISI-1055 & AISI-4340 steels

Abstract

This study focuses on the investigations of regression models and the comparative analysis in CNC turning of AISI-1055 & AISI-4340 steels under wet-condition in terms of average surface roughness (Ra) and material removal rate (MRR). In this study, optimal cutting-parameters were also investigated to minimize the “Ra” and maximize the “MRR” in CNC wet-turning of AISI-1055 & AISI-4340 steels using Taguchi design method. All the experiments were conducted with cutting tool-insert of coated cemented carbide under wet-cutting condition using conventional cutting fluid (flood coolant) and using L9 Taguchi orthogonal array (OA) design. A statistical analysis method, analysis of variance (ANOVA) was employed to investigate the influence of cutting-parameters on Ra and MRR. All the experimental data obtained for Ra and MRR were utilized to develop second-order regression-models. The developed regression-models for both Ra as well as MRR could be utilized to predict the responses in CNC wet-turning of AISI-1055 & AISI-4340 steels with a very small error. At last, a comparison between AISI-1055 and AISI-4340 steels on the basis of Ra and MRR obtained in CNC wet-turning were carried out. Comparative analysis between CNC wet-turning of both the materials show that the machinability of AISI-4340 steel is better than the machinability of AISI-1055 steel on the basis of Ra and MRR obtained