FITTING REGRESSION MODEL AND OPTIMIZATION OF CUTTING PARAMETERS IN ORDER TO ACHIEVE ECONOMICAL MACHINING OF A CRYOGENIC SOAKED MAGNESIUM ALLOY

Abstract

The ultimate aim of a production engineer is to produce a product which is economical in terms of overall cost of production. This motive of attaining economical machining is achieved by analysing the machining process and identifying critical cutting parameters which has definite influence on the machining operation and optimization of these parameters leads to obtaining an economical machining output. In present times, many industries are giving more importance in reducing the overall cost of production and in this regard reduction in weight of the work material has become necessary which in turn reduces the power consumption required for machining and hence leads to reduction in overall costs. Thus usage of light weight materials has garnered deep interest in the industries. This project deals with the turning of Mg AZ31B alloy for the above stated reasons. The objective of this work is to optimize the influencing cutting parameters like speed, feed, depth of cut and approach angle of the cutting tool by using experimental engineering design techniques like Taguchi method of orthogonal array, analysis of variance method to compute contribution of each of these parameters on the quality of machined output. The response variables taken up for this analysis were surface roughness, material removal rate, tool wear rate and machining time as all these factors governs the quality of the machined product and hence relates to economics of machining. Regression models have been developed in order to study about the mathematical relation between the input cutting parameters and each of the output variables. Contour plots have been drawn to study about interactions between the input cutting parameters and its impact on the output variables. In order to study the effect of cryogenic soaking on the work specimen Vickers hardness test has been performed to check the enhancement of the hardness before and after cryogenic soaking. The experimental data shows that surface roughness is mostly affected by approach angle of the cutting tool whereas material removal rate, tool wear rate and machining time were mostly affected by depth of cut. From the confirmatory test it was evident that Taguchi analysis helps in optimizing the output variables. It was also observed that cryogenic soaking suitably increases the hardness of the material thus making it more machinable.