Surface Roughness Prediction in Grinding: a Probabilistic Approach

Surface quality of machined components is one of the most important criteria for the assessment of grinding processes. The importance of 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 problem for grinding. In this study, a new analytical surface roughness model is developed on the basis of the stochastic nature of grinding processes. The model is 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 using AISI 4340 steel in surface grinding.