A computer vision system for saw blade condition monitoring

Tool condition monitoring is a key component of predictive maintenance in smart manufacturing. Predicting excessive tool wear machining processes becomes increasingly difficult if different materials need to be processed. We propose novel computer vision-based system for saw blade that independent the processed and combines deep learning with classic vision. Our approach allows accurate which can further used maintenance. Additionally, classify defect types such as missing teeth, thus preventing production scrap parts.