Abstract
Surface roughness is a critical indicator to evaluate the quality of 4H-SiC grinding surfaces. Determining surface roughness experimentally is a time-consuming and laborious process, and developing a reliable model for predicting surface roughness is a key challenge in 4H-SiC grinding. However, the existing models for surface roughness in wafer rotational grinding fail to yield reasonable results because they do not adequately consider the processing parameters and material characteristics. In this study, we proposed a new analytical model for predicting surface roughness in 4H-SiC wafer rotational grinding, which comprehensively incorporates the grinding conditions and material characteristics of brittle substrate. This model derives and calculates the material's elastic recovery coefficient based on contact mechanics and elastic contact theory. Subsequently, we modified the grain depth-of-cut model by incorporating elastic recovery coefficient. Additionally, we analyze the distribution of the failure mode (ductile or brittle) on the surface of a material when the depth at which the material is cut instead follows a random distribution known as the Rayleigh distribution. To validate the accuracy of the established model, a series of grinding experiments are conducted using various grain depth-of-cut to produce 4H-SiC wafers with different surface roughness values. These results are then compared with those predicted by both this model and the traditional model. The findings demonstrate that the calculated data obtained from the proposed model exhibit better agreement with the measured data. This research addresses the need for an improved surface roughness model in 4H-SiC wafer rotational grinding.