Prediction model of tool wear volume in precision turning of ceramic particle reinforced aluminum matrix composites

In this work, a geometrical model is established to calculate the wear volume of cutting tool, into which the effects of rake angle, clearance angle, and tool nose radius are successfully integrated. And then the dynamic tool wear process is investigated based on the precision turning of 45 vol%SiCp/2024Al with PolyCrystalline Diamond (PCD) tools. A new evaluation parameter, i.e., tool wear volume rate, is defined to compare the wear resistance of tools with varied geometrical parameters. Experimental results show that tool wear volume rate is closely related to the grain size of PCD and tool rake angle. However, it is independent on tool nose radius. Subsequently, the prediction model of tool wear volume as a function of cutting length is further formulated to characterize the dynamic evolution of tool wear. The validation experiments show that the prediction accuracy is satisfactory, i.e., that the average prediction error is only 6.13%, which indicates that the calculation method and prediction model of tool wear volume proposed in this work are effective. Finally, the application scope of the developed prediction model is further specified.