Optimization of Machining Parameters using Genetic Algorithm

Abstract

The present competitive environment forces the organizations to stand on alert every minute and use its resources (man, material, and machine) to their best possible extent. The present work aims to explore genetic algorithm (GA) as a method for optimizing machining parameters selection. The algorithm searches for the best solution in terms of cutting speed and feed with the aim of optimizing an objective function. The objective functions considered here take into account optimizing anyone or a weighted sum of the two significant criteria- total production cost and total production time, in single pass turning operation. The GA technique used for optimization purpose provides an efficient and promising tool in view of high degree or non-linearity in the objective function. The technique, although applied here only on single pass turning, is applicable to much wider variety of machining situations.