Image-processing-based model for the characterization of surface roughness and subsurface damage of silicon wafer in diamond wire sawing

The damages of silicon wafer in diamond wire sawing have a significant impact on its mechanics, economy, and use properties, which should be evaluated accurately and quickly. A theoretical model is developed to determine the surface roughness Rz (ten-point mean height) and subsurface damage (SSD) depth by the fracture width of silicon wafer. The model takes into account the scratch groove direction and material pile-up effect of silicon wafer. A digital image processing method is integrated into the model to extract the fracture parameters of silicon wafer. Many silicon wafers are processed under different slicing parameters, for which the fracture parameters and surface roughness Rz are measured by confocal microscopy, and the SSD depth is measured with the method of cross-section scanning microscopy. The scratch-induced material pile-up height is evaluated by nanoscratching. The calculated and measured fracture parameters, surface roughness Rz, and SSD depth are analyzed by contrast. The result shows that the model can accurately and quickly determine the surface roughness Rz and SSD depth with an average relative error of less than 12.0% in 20 s. The distribution characteristics of fractures, surface roughness, and SSD are analyzed. The result shows that more fractures have relatively smaller fracture width, depth, length, or related SSD depth. The image-processing-based model would be a reasonable approach for estimating the damages in silicon wafers during wire sawing.