Automated detection of tool wear in machining and characterization of its shape

Flank wear VB_max remains one of the most essential and used metrics for measuring tool wear. VB_max is used to characterize tool wear rate, machinability of materials, the quality of machined surface. While VB_max measures the size of wear scar, the shape of the tool wear remains less used but not the least applicable for such characterization. However, quantification of the wear shape requires a more detailed information about the wear contour. This study develops an Image Processing solution for automated tool wear detection and applies Delaunay triangulation and implenarity parameter for characterizing the shape of the wear scar. Validation of the approach has been performed for machining stainless steel 316L without and with abrasive Al₂O₃ and SiO₂ inclusions. It is shown that VB_max and area parameters of the wear scar are insensitive to wear shape, while implenarity can accurately quantify irregularity, curvature, asymmetry of the scar. The results also show a strong relationship between the tool wear shape, the hardness and size of inclusions in the steel.