PARAMETRIC STUDY OF A CNC TURNING PROCESS USING DISCRIMINANT ANALYSIS

Abstract

In the present day manufacturing scenario, computer numerical control (CNC) technology has evolved out as a cost effective process to perform repetitive, difficult and unsafe machining tasks while fulfilling the dynamic requirements of high dimensional accuracy and low surface finish. Adoption of CNC technology would help an organization in achieving enhanced productivity, better product quality and higher flexibility. In this paper, an endeavor is put forward to apply discriminant analysis as a multivariate statistical tool to investigate the effects of speed, feed, depth of cut, nose radius and type of the machining environment of a CNC turning center on surface roughness, tool life, cutting force and power consumption. Simultaneous discrimination analysis develops the corresponding discriminant function for each of the responses taking into account all the input parameters together. On the contrary, step-wise discriminant analysis develops the same functions while considering only those significant input parameters influencing the responses. Higher values of hit ratio and cross-validation percentage prove the application of both the discriminant functions as effective prediction tools for achieving enhanced performance of the considered CNC turning operation.