A new surface roughness prediction model for ceramic grinding

Abstract

Product quality assurance is a very important concern in industries these days. Surface quality is an important constituent of overall product quality in ceramic grinding. Surface roughness is one of the major quality attributes of a ground product and hence it is used to determine and evaluate the quality of the product. Although the surface roughness evaluation has been standardized, establishment of a model for reliable prediction of surface roughness is still a key issue. This paper presents a new analytical model for the prediction of arithmetic mean surface roughness based on the stochastic nature of grinding process, governed mainly by the random geometry of grain and 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 silicon carbide grinding.