Authors: P.J. Pawar; D.P. Rai-Kalal
Addresses: Production Engineering Department, K.K. Wagh Institute of Engineering Education and Research, Nasik, Maharashtra-422003, India ' Production Engineering Department, K.K. Wagh Institute of Engineering Education and Research, Nasik, Maharashtra-422003, India
Abstract: Selection of appropriate combination of process parameters in any machining process is a crucial task as it significantly affects the process performance. In the present work, an attempt is made to optimise the process parameters of grinding process. A well-known multi-objective optimisation technique known as non-dominated sorting genetic algorithm II (NSGA-II) is applied to obtain the optimum values of process variables such wheel speed, work-piece speed, depth of dressing, and lead of dressing in order to improve the process performance in terms of production cost, production rate, and surface finish. Various process constraints such as thermal damage of work-piece, wheel wear, and machine tool stiffness are also taken into account.
Keywords: grinding; multi-objective optimisation; non-dominated sorting genetic algorithm II; NSGA-II; genetic algorithms; process parameters; wheel speed; workpiece speed; dressing depth; dressing lead; production cost; production rate; surface finish; surface roughness; surface quality; thermal damage; grinding wheel wear; machine tool stiffness.
International Journal of Metaheuristics, 2013 Vol.2 No.2, pp.123 - 140
Received: 17 Mar 2012
Accepted: 19 Sep 2012
Published online: 23 May 2013 *