Modelling and statistical analysis of surface roughness by Taguchi and RSM techniques in hard turning of AISI 52100 steel with multilayer coated carbide insert

Abstract

The statistical data of surface roughness (Ra, Rz) associated with the machining parameters (cutting speed, tool nose radius, depth of cut and feed) during turning of AISI 52100 steel using multilayer coated carbide inserts was experimentally modelled in this study. Analysis of variance (ANOVA) was employed to ascertain the significance of the cutting parameters whereas response surface methodology (RSM) depending on Taguchi design of experiments was employed to optimise the factors influencing surface roughness. The models established for approximation of Ra and Rz were 91.02% and 92.42% reliable. The most influencing parameter for Ra was tool nose radius followed by feed with contribution of 33.83% and 32.50% respectively, while the contribution of tool nose radius and feed rate for Rz was 39.21% and 33.46%. The optimum combination obtained through multi-response optimisation for minimum roughness was 70 m/min cutting speed, 0.05mm/rev feed, 0.1mm depth of cut and nose radius of 1.2 mm.