Fraunhofer IPA offers various technologies for the inline quality control of manufacturing processes. The developed concept evaluates the quality of parts at periodic intervals based on fluctuations in signal datasets from the process.
The aim is to recognize faulty process and production states at an early stage in order to avoid defective parts from being dispatched. The ability to intervene in processes promptly also enables potentials regarding productivity, competitiveness, resource conservation and cost-effectiveness to be exploited.
To reduce adaptation requirements and thus shorten start-up times, signal datasets from the production process are evaluated with special two-step classifiers. Even with initially-reduced sample datasets, the system is capable of monitoring the production process adequately and can be further trained if necessary.
The system technology has been integrated and verified at partner companies in different manufacturing processes. The focus is especially on small and medium-sized enterprises, which produce high-quality components in small quantities.
The system also demonstrates how the immediate recognition of faulty process or product states can contribute significantly towards improving productivity, competitiveness, resource conservation and cost-effectiveness.