Developing an easy-to-use image-based system for offline tool-wear detection

Tool wear plays a critical role in the machining industry. Worn tools can significantly affect the workpiece's dimensional accuracy. However, with the increasing popularity of operating cutting machines without enough machining background, such as the technician operating the milling machine in a dental clinic, nonprofessionals may not know the tool replacement timings to reduce the production waste caused by the worn tools. If a tool wears too much so that the finished workpiece is dimensionally inaccurate, then rebuilding another workpiece will cost valuable time and resources. On the other hand, if a tool is replaced too early, the cost of purchasing tools will increase. This research aims to address these challenges. The objective of this research was to develop an easy-to-use image-based system for tool wear detection, which was built with inexpensive components and can automatically measure cutting-edge widths of cutting tools using image processing techniques. The practical implication of the proposed tool wear detection system is that it can automatically measure cutting-edge widths at various cutting depths of a tool, which can allow nonprofessionals to understand how much dimensional change has been made before and after the tool is used. The repeatability of the proposed system was only 4 µm, which means that the system can effectively detect the width change greater than 8 µm at a 95% confidence level. For the 2 mm ball end milling tool used in the research, the width difference from a new tool to an end-of-life tool was 57 µm. The proposed system can detect the width difference caused by tool wear so that the technician can replace the tool in time using the proposed system.