Empirical Modelling for Prediction of Work piece Surface Roughness and Cutting Tool Temperature in Turning Carbon Steel

Abstract

To increase cutting tool life and improve workpiece surface quality, an empirical model was proposed to predict workpiece surface roughness and cutting tool temperature by discovering an empirical equations that depends upon the experimental results of turning carbon steel. These empirical equations predict values; and describe the behaviour of workpiece surface roughness and cutting tool temperature. The experimental work involves turning carbon steel (ASTM Standard A105) by measuring workpiece surface roughness and cutting tool temperature at different cutting speed, feed rate, and depth of cut that consider the major cutting parameters. The results indicated that cutting speed and feed rate has a major effect on workpiece surface roughness and cutting tool temperature. Also, a comparison between experimental and predicted results was made, which show a good agreement, i.e the correlation coefficients reached to 0.9894 for surface roughness and 0.9943% for temperature.