Grinding process can achieve minimal material removal quantity and multiple material removal mechanisms simultaneously, which makes it extremely popular in industrial applications to meet the requirements of high dimension precision, excellent surface quality and rigorous tolerance. However, due to the randomly-sized and randomly-distributed abrasive grains, an accurate ground surface prediction model remains a significant challenge by considering the actual microstructure of grinding wheel. This research aims to develop a novel surface prediction model to take into account the random nature of the grain size and its distribution in grinding wheel. The generation of ground surface is modeled by calculating the transient trajectory of grain in the whole contact zone. Micro grain-workpiece contact mechanism is revealed in terms of the typical stages of rubbing, plowing and cutting to determine the ground surface morphology. Grinding experiments were performed to compare with the predicted surface morphologies. The proposed model was further validated in the terms of surface topography, roughness and material removal rate. Additionally, material removal mechanism associated with surface generation has been explored by the predicted ground surface and material removal rate under different grain-workpiece interaction states. The provided model is further employed to examine the impact of the randomness of grain size and distribution and grinding parameters on the surface roughness. Thus, the research provides fresh insights into understanding the underlying mechanism in different grain stages as well as revealing the transient contact mechanisms in generating ground surface integrity.
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