Statistical analysis of surface roughness in turning based on cutting parameters and tool vibrations with response surface methodology (RSM)

In this paper, we present an experimental study to determine the effect of the cutting conditions and tool vibration on the surface roughness in finish turning of 32CrMoV12-28 steel, using carbide cutting tool YT15. For these purposes, a linear quadratic model in interaction of connecting surface roughness (Ra, Rz) with different combinations of cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration, in radial and in tangential cutting force directions (Vy) and (Vz) is elaborated. In order to express the degree of interaction of cutting parameters and tool vibration, a multiple linear regression and response surface methodology are adopted. The application of this statistical technique for predicting the surface roughness shows that the feed rate is the most dominant factor followed by the cutting speed. However, the depth of the cut and tool vibrations have secondary effect. The presented models have some interest since they are used in the cutting process optimization.