Multivariate empirical modeling of interaction effects of machining var-iables on surface roughness in dry hard turning of AISI 4140 steel with coated CBN insert using Taguchi design
Keywords: multivariate analyses, surface quality, data-driven modeling, dry hard turning, Taguchi design
AbstractThe most important measures of surface quality during the machining process are changes in the average surface roughness and maximum peak-to-valley height caused by such machining variables as cutting speed and feed rate. This study quantifies the interaction effects of the machining variables on surface roughness in dry hard turning process of AISI 4140 steel with CBN7015 inserts. The Taguchi experimental design, (multivariate) analysis of variance, and multiple (non-)linear regression models were combined in the quantification and modeling of interaction effects on surface roughness in dry hard turning process. There existed a significant interaction effect between cutting speed and feed rate in determining the behavior of the response variables.