New DFG Priority Programme headed by Paderborn University
The German Research Foundation (DFG) has set up six new Priority Programmes to begin this year. These initiatives are examining the scientific fundamentals of specific current research areas across multiple sites. Prof. Dr.-Ing. Iris Gräßler, a researcher at Paderborn University, is heading up one of the programmes. The aim of this large-scale project is to increase the performance of interdisciplinary product creation. This involves overcoming the complex challenges of the circular economy, global dependencies and the digital transformation in mechanical and plant engineering. It focuses on basic research into the processes and methods of data science and artificial intelligence (AI), which will be able to augment human capabilities in the future. The six programmes are being funded for an initial period of three years with a total of 44 million euros.
Established procedures reaching their limits
‘Technical systems are increasingly interdisciplinary, complex and more and more interconnected. Products and product systems therefore require multi-objective optimisation. Sustainability and circular economy requirements are also further increasing complexity levels’, explains Gräßler, who holds the Chair of Product Creation at Paderborn University’s Heinz Nixdorf Institute. The scientist notes that many of the resulting requirements only first emerge at a later point in a product’s lifecycle, e.g. during use, decommissioning or material recycling. However, upstream and downstream resource consumption and the future availability of recycled materials (substances obtained from recycling plastics) must be taken into account during the product creation process. Product developers bear overall responsibility for this, as key players in the circular economy. Gräßler gives a specific example: ‘Today, electric vehicles need to have a large range, be usable for a long time, and be reusable or recyclable at the end of their service life. However, at the product creation stage, there are insufficient products available to be able to evaluate driving and user behaviour, charging cycles, wear and tear, or the technological maturity of recycling processes. Technical systems must be designed to meet the requirements of future markets, as well as engineered for production, maintenance and recycling technologies. The effectiveness of previously established engineering processes (such as heuristics, modelling and simulation) is now reaching its limit in some cases.’
New knowledge for future processes
These various challenges mean that it is vital to increase the performance and efficiency of interdisciplinary product creation. Researchers are seeking to achieve this by systematically incorporating data. Using data science and AI, they can for example map relevant connections between product use and product components’ reincorporation into the material cycle. Gräßler: ‘New concepts are needed to deal with extreme, rapidly changing data in a variety of formats in product and production system development, and to prepare for the future data situation in good time: what data do we need now and what will need soon? What information do we need to collate about what new knowledge so that it can be incorporated into future development processes?’ In the future, AI and data science methods (alongside human skills) could be used in combination with existing processes to increase the efficiency of product creation.
