Could you briefly introduce yourself and tell us how long you’ve been working at Fraunhofer IIS in Dresden?

I’m Martin and I’ve been working at Fraunhofer IIS at the Dresden site since April 2024, so for a little over a year, in the Industrial Data Analysis Systems group. I’m currently working on the use of digital twins for industrial processes. By »digital twins«, we mean virtual models of complex systems, which may be machines or entire production facilities. The models bring together wide-ranging data and sources of information in order to perform tasks such as error analysis or the prediction of operating states.

What topics are you work here at the division?

Specifically, my work is about breaking down data and knowledge silos and gaining valuable insights into how they are connected. To develop and implement a digital twin of this kind, however, you need many different perspectives on the processes. What data sources exist? What system architecture is appropriate for the systems? How does the data need to be semantically described to allow networking? And, last but not least, what added value does all this effort generate? Here at the division, these are the all the sorts of questions we work on. In order to explore the topic – and its opportunities and requirements – in tangible form, we’re currently developing a demo production environment in our laboratories as part of the AI Application and Test Center. I provide support here to the technical project management.

What do you find most exciting about your work?

There are two things that excite me the most. First, I like the practical and transfer-oriented approach here at Fraunhofer – because this approach has had a less important role in my academic career so far. It offers a completely new perspective when it comes to solving problems but also helps us to think about economic relevance from the outset. Second, I find the diverse opportunities for the industrial use of AI extremely exciting. As a trained process engineer, I really enjoy gaining an understanding of wide-ranging processes – from small-scale production processes to large-scale process engineering – and combining this knowledge with AI methods and applications.

What topics do you see yourself researching in the future?

Working with digital twins is an exciting prospect for me. There’s still considerable potential here to drive advances in digitalization and the use of AI. Digital processes can be modeled quickly and automatically, and tailor-made AI tools can be introduced easily. There are still all sorts of research and development opportunities in this area.