Observing Tool Bit Conditions in Turning Process through OpenCV Programming Function

Machine vision provides flexibility and further automation options to manufacturers. It helps detect product defects, complete a different number of tasks efficiently. The goal of this work was to develop a machine vision program that would monitor the state of the tool bit state and signals it through a software pop-up when the tool bit exhibited anomaly while cutting. The program would sense when the tool bit shows an anomaly of its sharpness while cutting. Canny algorithm and thresholding were the techniques to perform video analysis. Canny edge detector algorithm was used to change the RGB image to a grayscale-based image. The image would display only the object's edges so that the tool bit's sharp edge was visible and was analyzable for tool wear condition. The monitoring of the tool wear condition using OpenCV programming functions was proven workable. Further codes enhancements are needed to provide an effective program and to produce reliable results.