Defect-sensitive testing data analysis method for industrial robots quality inspection

摘要

Industrial robots play important parts in modern industries to increase factory capacity and guarantee final product quality. The qualified industrial robot product is critical to promise the OEE (overall equipment efficiency) at customer site. Therefore, quality inspection is the indispensable part in robot manufacturing. To guarantee superior robot quality and excellent customer experience, the defect-sensitive testing method is proposed to detect robot defect issues, including defects of incoming materials and problems of robot assembly. Two main technologies applied here to improve defect sensitive are segmentation of running cycle and integration of physical model and data model. The results from the testing data analysis method could not only show the pass or not information of the detected robot, but also guide how to fix the problem if any defect issue is detected. This could sharply reduce dependence on expert knowledge and personal experience.