Machinability investigations on high chrome white cast iron using multi coated hard carbide tools

Abstract

This study investigated the performance of multilayer hard coated carbide tool and multi-response optimization of the turning process for an optimal parametric combination to yield the minimum cutting forces and machining power with a maximum material removal rate (MRR) using Taguchi and artificial neural network (ANN) methods. In recent times, high chrome white cast iron finds increasing applications in aerospace, mining, mineral process industries. Its machinability using carbide insert (TiC/TiCN/Al2O3) cutting tool has been studied. The influences of cutting parameters on the cutting forces, MRR and machining power of the process have been analyzed using analysis of variance and the results are correlated using ANN. Linear regression method was used to establish the relation between the cutting parameters and the process responses. The confirmation test reveals that, the accuracy of prediction of ANN is better than that of the regression analysis. In view of the good performance of the carbide tools (at optimum conditions), it can replace the cosly CBN, with improved economic benefits. 2014 Indian Institute of Metals.