Physics-based modeling and mechanism of polycrystalline diamond tool wear in milling of 70 vol% Si/Al composite

Abstract High-volume fraction silicon particle-reinforced aluminium matrix composites (Si/Al) are increasingly applied in aerospace, radar communications, and large-scale integrated circuits because of their superior thermal conductivity, wear resistance, and low thermal expansion coefficient. However, the abrasive and adhesive wear caused by the hard silicon reinforcement and the ductile aluminium matrix leads to significant tool wear, decreased machining efficiency, and compromised surface quality. This study combines theoretical analysis and cutting experiments to investigate polycrystalline diamond (PCD) tool wear during milling of 70 vol% Si/Al composite. A key contribution of this work is the development of a tool wear model that incorporates reinforcement particle characteristics, treating them as ellipsoidal structures, which enhances the accuracy of predicting abrasive and adhesive wear mechanisms. The model is based on abrasive and adhesive wear mechanisms, and can analyze the interaction between silicon particles, aluminium matrix, and tool components, thus providing deeper insights into PCD tool wear processes. Experimental validation of the model shows a good agreement with the results, with a mean deviation of approximately 10%. The findings on the tool wear mechanism reveal that, as tool wear progresses, the proportion of abrasive wear increases from 40% in the running-in stage to 75% in the rapid wear stage, while adhesive wear decreases. The optimal machining parameters of 120 m·min –1 cutting speed ( v c ) and 0.04 mm·z –1 feed rate ( f z ), result in tool life of 33 min and surface roughness ( S a ) of 2.2 μm. The study uncovers the variation patterns of abrasive and adhesive wear during the tool wear process, and the proposed model offers a robust framework for predicting tool wear during the machining of high-volume fraction Si/Al composites. The research findings also offer key insights for optimizing tool selection and machining parameters, advancing both the theoretical understanding and practical application of PCD tool wear.