Explainable Artificial Intelligence for human-AI collaboration

As a society, we have come to notice the influence and impact Artificially Intelligent (AI) agents have on the way we live our lives. For these AI agents to support us both effectively and responsibly, we require an understanding on how they make decisions and what the consequences are of these decisions. The research _field of Explainable...

Automated Defect Analysis using Optical Sensing and Explainable Artificial Intelligence for Fibre Layup Processes in Composite Manufacturing

In modern aircraft, structural lightweight composite components are increasingly<br/>used. To manufacture these components in a costeffective way, robust production systems for the manufacturing of complex fibre composite components are necessary. A rather novel but already established process for fibre material deposition is the Automated Fibre...

Cross-evaluation of a parallel operating SVM – CNN classifier for reliable internal decision-making processes in composite inspection

In the aerospace industry, automated fibre laying processes are often applied for economical composite part fabrication. Unfortunately, the current mandatory visual quality assurance process takes up to 50% of the entire manufacturing time. An automised classification of manufacturing deviations using Neural Networks potentially improves the...

Interactive Natural Language Technology for Explainable Artificial Intelligence

We have defined an interdisciplinary program for training a new generation of researchers who will be ready to leverage the use of Artificial Intelligence (AI)-based models and techniques even by non-expert users. The final goal is to make AI self-explaining and thus contribute to translating knowledge into products and services for economic...