Research on Milling Parameter Optimization and Wear of PCD Tools for SiCp/Al Composites

To investigate the wear behavior of Polycrystalline Diamond (PCD) tools during the milling of high volume fraction silicon carbide particle-reinforced aluminum matrix composites (high volume fraction SiC _p /Al) and realize the prediction of tool wear, an orthogonal experiment and multiple linear regression analysis were adopted. The factors influencing tool wear and a tool wear prediction model were obtained, followed by the F-test and R² test for the model. The test results indicate that the model is statistically significant overall. Through orthogonal experiments, the effects of milling parameters on cutting force, workpiece surface roughness, and tool wear amount were determined. By comparing the relative error between the actual tool wear amount and the wear amount predicted by the model, it was found that the average error is within 5%, which verifies that the model possesses the preliminary capability of predicting tool wear. The experimental results show that in practical milling operations, a reasonable selection of milling parameters can effectively reduce workpiece surface roughness and tool wear, thereby prolonging tool life.