Optimization of Machining Process Parameters in Hard Turning of AISI D3 Tool Steel

Abstract

Machining operation is still irrefutably vital process in manufacturing, that involves complex relation of input parameters (like cutting speed, feed rate, depth of cut, nature of cooling, etc.) to output parameters (like surface finish, tool life, tool wear, machining time, machining cost, etc.). Numerous efforts were noticed in literature, to relate these parameters with each other so as to implement cost effective machining with least efforts. This paper presents one such attempt made towards optimisation of cutting parameters for turning of AISI D3 under wet environment using reliable optimization techniques like shifted Hammersley sampling (Screening) and multi-objective genetic algorithm (MOGA). The design of experiments (DOE) was established based on central composite design (CCD) with three levels for each input parameter. The results of experiments were verified by simulating similar machining conditions within a virtual machining facility eased by CAE software package ‘Deform 3D’. The optimisation of cutting parameters is carried out in ‘ANSYS workbench 15 DesignXplorer for optimization’. Various response surfaces are generated to understand the effect of input parameters on each output parameter that is to be optimized. The optimum values suggested by each optimization technique are compared so as to arrive at the best feasible optimum value for wet machining.