Development of a tool outline measurement system by using vision-based algorithms

Abstract Current domestic reground tool measurement methods either rely on the operator's experience or involve analyzing signals from multiple sensors to determine the tool condition. Despite the availability of numerous measurement techniques, accurately determining the condition of reground tools' condition remains challenging due to the varying time, equipment requirements, and the inherent difficulty in analyzing complex signals. Consequently, collecting comprehensive tool data becomes imperative. This study introduces a novel approach by developing a method for measuring the outer edge of tools, enabling precise condition assessment through a vision-based measurement system. This system not only aims to mitigate the errors commonly associated with manual measurements in the manufacturing sector but also seeks to enhance the process analysis efficiency. By doing so, it aims to significantly decrease the rejection rates of tool measurements and streamline the analysis process, potentially extending tool life and improving performance management. This method promises to contribute to more sustainable manufacturing practices by optimizing tool usage and reducing waste.