NSGA-II Approach of Optimization to Study the Effects of Drilling Parameters in AISI-304 Stainless Steel

This paper highlights the parametric appraisal for burr height and circularity in drilling of hole on AISI-304 stainless steel using Non-dominated sorting genetic algorithm (NSGA). The major problem arises in drilling operation is the formation of burr and taper which seriously affect the quality of holes in practical applications. The present paper investigates the influence of drilling parameters viz., spindle speed, feed rate, and drill bit diameter on burr height and circularity. A total of twenty numbers of experiments were performed based on face centered central composite design (FCCD) of response surface methodology. Generally, the response surface methodology is used for modeling and analyzing manufacturing problems to understand the parametric effect on process responses individually, but it is unable to handle the multi-response problems. To overcome this limitation, proposed NSGA II is used for evaluation of optimal parametric combination in this study. The NSGA II is an improved approach of genetic algorithm (GA) for multi-objective optimization of process responses where non-dominated solutions having high crowding distance are used to provide diversified Pareto-optimal solutions. Analysis of variance shows that spindle speed significantly influence for the circularity of the drilled hole whereas all the parameters like spindle speed, feed rate and drill diameter influence on burr height. The optimal non-dominated set of solutions obtained through the NSGA II gives the manufacturer more flexibility in decision making in manufacturing process.