Abstract

Constant innovations and rethinking of existing systems and processes are essential for the fulfilment of business goals of automotive groups - also for the field of quality assurance. In the context of quality assurance of spot welded joints, the basic tasks of inspection processes are to support the definition of welding parameters, the monitoring of welding results, the optimization of the inspection process and, as a consequence, the reduction of costs and production time. Rigid and manual processes, as they are still used in many areas of quality assurance, are based on laboratory conditions. They are built on general assumptions and are a generic procedure without the possibility of learning processes. If these processes developed in the laboratory encounter production realities, they reach their limits and waste valuable efficiency potential. For example, conventional inspection processes are performed randomly and compare the actual with the target state and, in the event of a deviation, only provide the information of an existing process error. However, this pure information is no longer sustainable for intelligent production and requires a function extension in the sense of Industry 4.0. The goal in the sense of Industry 4.0 in this context is to recognize the root causes of these detected deviations, to provide information in real time and the subsequent intelligent reaction of the system. Artificial intelligence provides a learning system which, based on continuous analysis of production parameters, can not only detect predictive deviations of flexible environmental conditions, but also in a further step autonomously takes action. An example is the detection of weld spatter or sharp-edged areas of spot welds and the subsequent initiated grinding before inspection. This presentation focuses on the development of a robot-controlled module for the almost coupling agent-free inspection of spot welds with innovatively applied phased array technology in production (inline and offline) according to the demands of Industry 4.0.

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