From PLM to Digital Engineering
Olaf Sieg, Managing Partner at Detecon, talks to Prof. Detlef Gerhard, Head of the Chair for Digital Engineering at the Ruhr University Bochum
Olaf Sieg: Why was the Chair for Digital Engineering newly established? What is the focus?
Prof. Detlef Gerhard: I think that we wanted to anchor the topic of digital transformation even more firmly in the University of Bochum curriculum, specifically in our department, in view of the progress it is making in industrial companies.
The focus of the Chair for Digital Engineering is on research into methods, tools (i.e., functional IT processes), and models and processes for the development, production, and operation of technical systems. Our research activities are determined in particular by the interaction, integration, and use of technological drivers such as IoT, advanced data analytics, artificial intelligence, machine learning, and cloud services/platforms.
What has changed in the product lifecycle management [PLM] approach in recent years? What do you see as the future of PLM? What are the new functions and challenges?
As I see it, there haven’t been so many changes in the approach in recent years. Many companies have implemented or rolled out only a fraction of what the system providers can functionally cover with their solutions. There is still plenty of room to grow here, especially in midsize businesses. Since PLM intervenes in processes to a major extent, it needs a certain maturity level as has recently been discussed as well under the key word Industry 4.0.
I believe the future of PLM is in cloud-based solutions that can be initiated more simply and flexibly. The primary challenge continues to be the integration into the various disciplines with their special tools and models. New functions that are needed aim at managing every specific product and no longer the generic product class.
We both worked on the research project iViP, the first steps in virtual product development. So there has long been a vision of the 100% “product master” and boundaryless information management – what makes the digital twin new?
For me, the vision of the product master or, more recently, the digital twin and boundaryless information management are two different things. I have always had my doubts that there is only one master model or one digital twin that can represent all aspects or information from the product lifecycle in a single model. People have been chasing this idea since STEP and CIM days, and it is brought up for discussion every couple of years without ever finding a truly boundaryless solution. What we need is information management that is as boundaryless as possible, but in a federated context. That is precisely the issue that the basic approach of PLM solutions addresses.
What do you think about the topic of building information modeling [BIM] and the convergence of the domains mechanical engineering and civil engineering?
I have always rather flippantly said: BIM is PLM for civil engineers, just 20 years later. I also see the convergence of the domains mechanical engineering and civil engineering, and I find it fascinating. If we think about the development of production systems for instance, the machines and production facilities are always embedded in an environment of building case, supply, etc. And solely holistic planning makes good sense when viewed against the background of energy consumption optimization or similar tasks, for instance.
You are an assessor for the Excellence Initiatives – what skills will we need to cover in professional training in the coming years?
This is a genuine challenge that is the subject of intensive discussion in many of the departments I am familiar with. It is always a matter of professional depth versus breadth, of specialist versus generalist. There are many voices demanding, for example, that a degree in mechanical engineering must have a broader and more interdisciplinary structure. But since the scope of a degree program can cover only a limited space comprising depth and breadth, more breadth automatically means less depth. There is also the T approach that attempts to combine extensive breadth with depth in selected areas. Ultimately, however, we do not need either the one or the other, but the one as well as the other. We need specialists in machine construction, electrotechnology, or other disciplines, people who have detailed and profound know-how. Without them, we will be unable to master the complex challenges and the mega challenges. And we need generalists, system architects, engineers with interdisciplinary training; in other words, we must do the one thing without ignoring the other. This is often still lacking in the university landscape.