Surface Roughness Evaluation Using Factorial Design in Turning Operation

Abstract

In this work, a factorial experimental design was employed for studying the surface roughness of 195 BHN Cast Iron material in turning using High Speed Steel (H.S.S.) tool. Based on experimental results, first order predictive models for surface roughness with 95% confidence interval covering cutting speed varying from 16 to 64 m/min., feed from 0.075 to 0.3 mm/rev., depth of cut from 0.15 to 0.6 mm, and tool nose radius from 0.4 to 1.6 mm under dry condition were developed. The developed models have been tested by analyzing the variances. Based on the developed surface roughness models, contour curves were obtained to relate surface roughness to material removal rate for different cutting speeds and feeds which can be utilized for improving the efficiency of the cutting process.