“Team spirit will increasingly take center stage.”

“Team spirit will increasingly take center stage.”
Marginal Column
Prof. Dr.-ing. Dr. h. c. Albert Albers

Prof. Dr.-ing. Dr. h. c. Albert Albers has headed IPEK, the Institute of Product Engineering at the Karlsruhe Institute of Technology (KIT) since 1996. With regard to teaching, his work involves the restructuring of the curriculum and the targeted implementation of new teaching methods, which integrate the mediation of non-professional and social skills in the training in the field of design and product development. For this purpose, he has developed and implemented a holistic approach known as the “Karlsruhe teaching model for product development”.

Content

March 2016

 

Companies need to make product development and design more agile and also call established methods into question, according to Prof. Dr.-ing. Dr. h. c. Albert Albers. Here he gives us an overview of which changes are coming and how they can be handled.

The lone tinkerer is already a romantic image of yore nowadays, but how will the work of a designer look in the future?

Team spirit will increasingly take center stage. Because the ingenious Gyro Gearloose can no longer achieve the necessary technical depth. Specialists must pool their knowledge together on a common platform, upon which innovations can be created. Designers and software developers cannot solve problems alone, but can only find solutions together. This requires excellent communication skills. In addition, we need a new way of thinking: Until now, the designer waits for the specifications to base their solutions upon. That will no longer work in future because they need to take the technical and economic changes in the production environment into account early: during the development phase. To accomplish this, they must think about each customer individually, as well as the customer’s benefits and the underlying rationale for each specification.

Which factors will drive change most in the coming years?

Products and processes have changed greatly in many industries in recent years. New materials, mechatronic, adaptronic and optical-electronic mechanical systems are in use every bit as much as new digital production processes, manufacturing processes and automation capabilities. This applies, of course, to design engineers in particular as they are the designers in the product development process. For them, new opportunities for innovative product solutions arise by combining new technologies from different disciplines. At the same time, products are becoming more complex through the convergence of the virtual and the physical world. This not only leads to more complexity, it also offers greater potential. Hence, product development needs to become much more agile.

Are new approaches and tools required?

Yes. In terms of methodological approaches, we get a paradigm shift. For a long time, research meant a “blank piece of paper” approach, which always starts at zero. In reality, however, companies develop products on the basis of product generations. This concept requires and allows for new methods, approaches and strategies that can accommodate the required agility. We chased after the desire for a universal tool for 15 years – in vain. In the future, we’re going to need a lot of expertise in many different areas – with many different tools. We need to network this interdisciplinary know-how. One approach that I find quite future oriented is model-based systems engineering (MBSE)*. What’s still missing, however, are interfaces to the discipline-specific models, such as CAD product models. I also expect that we will develop machines and vehicles the same way that we develop software. That means that customers will already be on board during the testing phase with a beta version of the product. The challenge posed by the increasing complexity and the many subsystems that go on in larger systems is, of course, enormous.

How can security be guaranteed?

Pure virtual development in the form of physical and mathematical models is not sufficient to verify the risk during real operation. Therefore, I see great opportunities in bringing together complex real-time simulations with physical representations. A mega trend is that we can already work with physical representations, for example with rapid prototyping, in the very early phases of product development. This will strongly impact the development processes. And here too, the design engineer is going to play a central role.

How must training be adapted to these changes?

When it comes to training, we take into account the complexities of technology and management. However we need to focus not only on the undoubtedly important technical skills, but also on social skills. We need a sound foundation comprising the basics, but we must also impart interdisciplinary technological competence (keyword system-engineering approaches) at a high level. Furthermore, we have to abandon attempts at completeness. We cannot teach everything. However, it is necessary to create an active learning environment in which the trainers take on the role of learning companions for student teams.

The concept of Industry 4.0 is still in a state of flux. How do get it onto the right track today?

Companies must think ahead to the potential benefits, invest in research, and form networks with universities, suppliers, customers and partners. Business processes need to be checked for whether they allow the necessary agility. Moreover, the competency profiles should be adapted to the changed requirements. I see a great need for training, for example in the field of MBSE. For a long time, “lifelong learning” was only a catch phrase, but we won’t achieve Industry 4.0 without it. In the end, it’s people who create the innovations. We have to take them along and prepare them. And it’s possible to do that today. Now we have to bring the many interesting approaches to the companies. This will be a great challenge because we must consciously call into question things that we have so far done successfully.

*MBSE is the use of continuous, computer-interpretable models in cross-disciplinary system development. Intelligent, networked models that “know each other” are thus possible.