A multi-objective genetic algorithm (GA) approach for optimization of surface grinding operations

A genetic algorithm (GA) based optimization procedure has been developed to optimize grinding conditions, viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using multi-objective function model with a weighted approach for surface grinding process. The procedure evaluates the production cost and production rate for the optimum grinding condition, subjected to constraints such as thermal damage, wheel wear parameters, machine tool stiffness and surface finish. New GA procedure is illustrated with an example and optimum results such as production cost, surface finish, metal removal rate are compared with quadratic programming techniques. (C) 2002 Elsevier Science Ltd. All rights reserved.