Predictive Modeling of Surface Roughness in Grinding

Surface quality of the machined component is one of the most important criteria for the assessment of grinding process. The importance of the surface finish of a product depends upon its functional requirements. Since surface finish is governed by many factors, its experimental determination is laborious and time consuming. So the establishment of a model for the reliable prediction of surface roughness is still a key issue for grinding. In this study, a new analytical surface roughness model is developed on the basis of stochastic nature of the grinding process, governed mainly by the random geometry and the random distribution of cutting edges on the wheel surface having random grain protrusion heights. A simple relationship between the surface roughness and the chip thickness was obtained, which was validated by the experimental results of AISI 4340 steel in surface grinding.