Modelling and Optimization of Machining Parameters in Turning of H13 Tool Steel Using Response Surface Methodology-Desirability Function Approach

Abstract

In the present study, an attempt has been made to investigate the effect of machining parameters (cutting speed, feed rate, depth of cut and tool nose radius) on material removal rate and surface roughness in finish hard turning of H13 tool steel using carbide tool. The machining experiments were conducted based on response surface methodology (RSM) using face centered central composite design. A comprehensive analysis of variance (ANOVA) was used to fully identify the most influential parameters, and the adequacy of both fitted second order regression models were checked. 3D response surfaces and 2D contour plots were analyzed to completely observe the impact of combinatory different important interactive factors on the machinability behaviour under different turning conditions. The MRR and SR increase by increasing the cutting speed, feed rate and depth of cut. The depth of cut and feed rate are the most influential factors for increasing the MRR and SR respectively. Mathematical models for MRR and SR were developed by using Design Expert-9 software. Finally, a multi-objective optimization technique based on the use of desirability function (DF) technique was then applied to find optimal combinations of input machining parameters capable of producing the highest possible amount of MRR and lowest amounts of SR within process domain. The obtained predicted optimal results were then verified experimentally to compute confirmation errors. The values of relative validation errors, all being found to be quite satisfactory, 5.29% for MRR and 8.1% for SR, proves the efficacy and reliability of suggested approach.