Machined brittle material surface in grinding: modeling, experimental validation, and image-processing-based surface analysis

Abstract

The wide utilization of high-quality brittle material products has been closely related with mechanical grinding; however, the prediction of ground brittle material surfaces has been rarely studied before. To fill this gap, a prediction method of machined brittle material surfaces with substantial details including machined surface topography and morphology has been proposed in this study. The method has been established based on the determination of each grain-workpiece micro interaction (i.e., brittle and ductile interactions) and considered the random wheel topography and grinding kinematics. Validation experiments of typical brittle materials (including optical glass, zirconia ceramics, and glass ceramics) have proved the proposed method could, to a large extent, describe realistic brittle material grinding process and predict the machined surfaces in terms of (i) brittle and ductile region proportions, and (ii) roughness and waviness. To show the method advance, the influence of grinding conditions on ground brittle material surfaces at the grain scale has been studied. Some new insights, which could enhance existing understandings of the brittle material grinding process and guide industrial manufacture, have been gained. Besides, an image-processing-based method has also been proposed to automatically not only recognize but also measure the brittle and ductile regions on the ground brittle material surface. Moreover, the experiments proved the high measurement accuracy as well as high method applicability. Therefore, the detection method is also expected to be able to facilitate the development of smart and intelligent manufacture which requires the high-level automation.