Mensch vs. Maschine - Inline Qualitätssicherung im automatisierten Faserlegeprozess

Kurzfassung

Inline quality assurance methods are essential to improve part quality and reduce production time. Our image based inline quality assurance system provides the possibility to detect defects, categorize them by type and determine position and size of the defects. The output information can be used for part documentation, inspection assistance or in future applications for an inline manipulation of the systems behaviour. The flexible algorithm design is able to work for various materials and most quality inspection scenarios with a need to analyze and evaluate image based sensor data for inspection purposes. The highly parallel pre-analysis step is able to handle fast production velocities up to 1 m/s. The generation of knowledge about an optimal Sensor- and Algorithm design is part of our ongoing research.