Evaluation of Desirability Function Approach and Genetic Algorithm optimization of drilling characteristics on Duplex 2205

Abstract

Abstract This work deals with the development of an empirical model using Response Surface Methodology (RSM) for the independent parameters of drilling operation using Duplex 2205 using solid carbide tool in the CNC milling machine. The considered independent variables are spindle speed, feed rate and dependent variables are drilling time, entry burr height, entry burr thickness, exit burr height, exit burr thickness, surface roughness. After successful development of an empirical model, the process parameters are optimized with two different techniques named Desirability Function Approach (DFA) and Genetic Algorithm (GA). The spindle speed and feed rate were optimized as 270 rpm and 0.073 mm/rev. respectively through DFA and 468.85715 rpm and 0.13684 mm/rev., respectively through GA to minimize the responses. Later, the evaluation made between the optimization techniques to achieve the best responses which emphasize the superiority of GA over DFA.