Optimization of Cutting Parameters to Minimize Tooling Cost in High Speed Turning of SS304 using Coated Carbide Tool using Genetic Algorithm Method

Abstract

High speed turning (HST) is an approach that can be used to increase the material removal rate (MRR) by higher cutting speed. Increasing MRR will lead to shortening time to market. In contrast, increasing the cutting speed will lead to increasing the flank wear rate and then the tooling cost. However, the main factor that will justify the best level of cutting speed is the tooling cost which merges all in one understandable measurable factor for manufacturer. The aim of this paper is to determine experimentally the optimum cutting levels that minimize the tooling cost in machining AISI 304 as a work piece machined by a coated carbide tool using one of the non-conventional methods: Genetic Algorithm (GA). The experiments were designed using Box Behnken Design (BBD) with three input factors: cutting speed, feeding speed and depth of cut and three machining levels.Keywords: High speed turning, tooling cost, AISI 304, MRR 1 INTRODUCTION The development of advanced manufacturing technology has been growing up rapidly. One of the advanced approaches is by increasing the machining speed to increase material removal rate and then shortening time to market, lowering cost, high accuracy and better quality. One approach for reducing the machining time in machining is by increasing the speed turning. High speed turning is difficult to define due to the fact of materials are varied for their hardness. Therefore, high speed turning for one material may still be a low speed for another for example; the high speed for titanium is a low speed for aluminium [1]. However, these technologies should be justified by economic study. One of the most effective tools for economic study is by developing a cost model.In high speed turning the machining zone will be under high temperature and high sliding velocity. Therefore, the wear progress will be difficult to estimate and predict. However, the wear rate of the cutting tool may give unacceptable outputs and that will result a low quality of surface roughness [2]. However, estimating the tool wear is highly valuable to estimate the tooling cost due to the relationship of tool life and material removal during the life of tool. However, tool insert may reaches its life and should be removed and changed before the tool insert edge cannot give the desired and accepted roughness. If the cutting tool reaches its life very fast then this will lead to increase the tooling cost becomes. Therefore, the manufacturer needs to determine the best cutting levels that minimize the tooling cost. Thus, estimating and then determining the best levels of the independent factors in machining becomes critical and important.Determining the input level that can give the optimum values in machining process for one output response is very useful if the need for that response is important for one application but needs a validate and reliable mathematical model. In this research a regression empirical model will be developed and then the genetic algorithm method will be used to determine the minimum tooling...