Science-Journal visIT: Current insight into our research

In our science-journal visIT we inform you in a concentrated form about current focal topics of our research. Here you can find all issues in digital form (mainly in German language). If you wish, we will be happy to add you to the distribution list for the print edition - you will then receive visIT approx. four times a year free of charge. Simply write an e-mail to: publikationen@iosb.fraunhofer.de

AI is concerned with the creation of technical systems that can solve automated cognitive and intellectual tasks. The performance of today's computers makes it possible for AI methods to be significantly more effective and efficient than humans in designated scenarios, e.g., object recognition in images and videos, especially when correlations and patterns in huge amounts of data are to be learned.

But can AI methods also be used reliably and predictably in technical systems? How must one proceed as early as the design stage so that an engineer can rely on promised performance parameters? Fraunhofer IOSB is committed to researching and addressing these questions with a new discipline spanning several fields of expertise, AI Systems Engineering. This issue is dedicated to this topic.

The guest article by Lukas Schleicher of the VDMA or the Alliance Industry 4.0 Baden-Württemberg presents the perspective of SMEs in the use of Industry 4.0 and AI.

Julius Pfrommer defines the term and dimensions of AI Systems Engineering and explains the methodological challenges. Dr. Constanze Hasterok presents PAISE®, our new process model for AI Systems Engineering. Elisabeth Peinsipp-Byma and Nadia Burkart address the issue of explainability in complex AI-based systems, an essential building block for AI Systems Engineering.

In the final contributions, Christian Kühnert, Christian Weißenbacher, Masoud Roschani and Jens Ziehn present application examples of AI Systems Engineering for the domains of production and mobility. The practical examples come from our Competence Center for AI Systems Engineering Karlsruhe CC-KING, which we as Fraunhofer IOSB established together with the FZI Research Center for Information Technology and the Karlsruhe Institute of Technology (KIT). Companies and business-related organizations are involved via the Innovation Advisory Board. If you want to know more, drop by the CC-KING pages at https://www.ki-engineering.eu/en.

AI Systems Engineering - an exciting and forward-looking topic! We hope you enjoy reading our AI Systems Engineering issue and find it inspiring.

Content

The links will take you directly to the corresponding page of the ePaper (in German):

• Allianz Industrie 4.0 Baden-Württemberg
  Lukas Schleicher
• KI-Engineering – definition and challenges
  Julius Pfrommer
• PAISE® – the process model for AI systems engineering
  Constanze Hasterok 
• Toolkit for generating explanations for complex AI processes in the engineering domain.
  Elisabeth Peinsipp-Byma, Nadia Burkart
• AI systems engineering for steam and gas turbine monitoring
  Christian Kühnert
• AI systems engineering for the production of smart building materials
  Christian Weißenbacher
• Machine learning and simulation for automated mobility systems
  Masoud Roschani, Jens Ziehn