Ontologies and frameworks

In today’s industry, the use of knowledge-based systems (e.g. ontologies) is getting more and more important. With such a system it is possible not only to reason knowledge of specific production processes but also to connect such systems with time series databases of machine data (LIVE and historical) as well as simulation data. Such systems give therefore the opportunity for a fundamental use of connected data within Industry 4.0.

Synthetic data generation for ML-based defect detection (Nantwin): Automated quality assurance is indispensable in today's production plants. Commonly used visual error detection models are increasingly ML-based. To train these ML models, extensive amounts of data are required, which are often not available. The synthetic data generation provides a solution to this problem. The research focuses on a framework that can synthesize images that depend on multiple input modalities.