Experimental Investigation and Predictive Modeling of Tool Wear in Turning of Hardened Steel

Abstract

The turning of hardened steel (above 45HRC) under dry environment has received newlineconsiderable critical attention due to its effective metal removal with good surface newlinequality along with dimensional accuracy. Though there are some major issues with the newlinedry turning of hardened steel using ceramic and coated carbide tool inserts, until newlinerecently, there has been hardly any evidence that a hybrid ceramic insert has been used newlinein turning of AISI D3 steel in a dry environment. The present work took a step ahead in newlinethis direction and studied the influence of cutting variables on machining responses. In newlinethis study, the horizontal hard turning using AISI D3 hardened steel has been performed newlineusing TiN coated Al2O3+Ti(C,N) ceramic tool insert. Three sets of cutting parameters newlinehave been selected from the extensive study of literature reviews with the feasible range newlineselection for cutting speed, axial feed rate and depth of cut after adequate number of newlinetrial experiments. The machined surface roughness with corresponding chip newlinemorphology and tool wear have considered as machining performance parameters newlinewhereas cutting force as an economic factor in this work. The parametric influence has newlinebeen studied using Taguchi design of experiments. Finally, an attempt was made to newlinedevelop mathematical regression models between machining performance parameters newlineas a function of process variables using response surface methodology. There were newlinevarious parametric optimization studies on machining process optimization, but newlinestochastic particle swarm optimization was not highly used though it has the capability newlineto search the hidden process features in different engineering fields. Thus, multi- newlineobjective optimization of the hard turning process has been processed using this newlineintelligent algorithm. newline newline