Multi Objective Optimization of Cutting Parameters in Turning Operation to Reduce Surface Roughness and Cutting Forces

Abstract

Turning is one the most important machining operation in industries. The process of turning is influenced by many factors such as the cutting velocity, feed rate, depth of cut, geometry of cutting tool cutting conditions etc. The finished product with desired attributes of size, shape, and surface roughness and cutting forces developed are functions of these input parameters. Properties wear resistance, fatigue strength, coefficient of friction, lubrication, wear rate and corrosion resistance of the machined parts are greatly influenced by surface roughness. Forces developed during cutting affect the tool life hence the cost of production. In many manufacturing processes engineering judgment is still relied upon to optimize the multi-response problem. Therefore multi response optimization is used in this study to optimization problem to finds the appropriate level of input characteristics.
The objective of this project is to evaluate the optimal setting of cutting parameters cutting velocity (N) , depth of cut(d) , feed(f) and variation in principal cutting edge angle (Φ) of the tool to have a minimum cutting force and surface roughness(Ra)
In this project dry turning of aluminium 6061 as a work piece and carbide insert tool (SCMT 09T308-TN5120) is performed. The range of cutting parameters are cutting speed(11.86, 18.65,30.52m/min) ,feed rate(0.044,0.089,0.178 mm/rev), depth of cut(0.5,0.75,1.0mm) and the angle (0,3,6 degree)
This study highlights the use of Fuzzy logic and use of Taguchi design of experiment to optimize the multi response in turning operation. For this purpose Taguchi design of experiment was carried out to collect the data for surface roughness and various cutting forces. The results indicate the optimum values of the input factors and the results are conformed by a confirmatory test