Extending the Welding Seams Detection as Preparation Towards the Digital Twin Technology

Abstract

Detection and identification of defects in manufactured products, a task related to the basic requirements of quality management systems. By moving to higher levels, under the right conditions, these defects can be avoided, for example, by preventing manufacturing defects from occurring. Quality control and monitoring of welds are closely linked to the requirements of Industry 4.0. In the case of welding processes, quality assurance is a multifaceted area, including not only the analysis of input parameters but also the quality of the weld surface. By superimposing the point clouds of the parts under test, geometric features are generated to the initial manufacturing parameters to help increase manufacturing efficiency. In our work, the information data recorded by the data acquisition framework, which is captured during the welding process, is integrated with the outputs of the point cloud characteristics of the examined by the structured light scanning technology, as well as the value of the seam width magnitude extracted by the image recognition algorithms. This contributes to the possibilities of broadening the seam detection processes.