DefinePK

Abstract

In highly competitive and rapidly changing scenario of manufacturing industries, nowadays the selection of machining operation, process parameters and application of optimization techniques plays a major role to increase the quality of a product. To achieve the quality product, the machining process parameters such as the cutting speed, depth of cut, feed rate, tool angle, type of lubrication used etc plays a major role. This paper gives an overview and the comparison of the evolutionary optimization techniques to optimize machining process parameter of both turning and facing operation in CNC and conventional lathe. Recent heuristic techniques are considered for optimization purpose, Response Surface Methodology (RSM) Genetic algorithm (GA), simulated annealing (SA), Particle swarm optimization (PSO), Ant colony optimization (ACO) and artificial bee colony (ABC) algorithm. Literature found that RSM and GA were widely applied by researchers to optimize the machining process parameters. The proposed research was beneficial for industries to determine the optimal cutting parameters in order to minimize the costs incurred and improving productivity of manufacturing firms and improve the quality of the process and product.