Support of Image-Based Quality Assessment in Discrete Production Scenarios through AI-Based Decision Support

This paper is based on results obtained during the research project IQ-Control. The main objective of the project targets the enrichment of a conventional perception-based 3D line scanning sensor data with methods of deep learning, in order to identify quality defects in discrete production scenarios in real-time. In the coming years, this process should help to preserve resources and further reduce material consumption, especially for large quantity production scenarios.