Optimization of multipass turning operations using Particle Swarm Optimization

In this paper, a Particle Swarm Optimization (PSO) algorithm is implemented to optimize the multipass turning process which has rough machining and then a finish machining. The objective function considered is minimization of unit production cost that optimizes the machining parameters. The performance of the PSO is evaluated by comparing it with genetic algorithm (GA) and simulated annealing (SA) algorithm reported by earlier researchers.