Die Nutzfahrzeugproduktion durch Nutzung künstlicher Intelligenz stärken
The use of artificial intelligence promises process improvements in commercial vehicle production. To this end, the Commercial Vehicle Cluster (CVC) Southwest, together with the Rhineland-Palatinate Ministry of Economic Affairs, Transport, Agriculture and Viticulture, is funding a research project with researchers from TU Kaiserslautern and companies.
Commercial vehicle production is characterized by a high number of variants, which is accompanied by a small number of individual variants. This leads to a high level of complexity, which often results in a high susceptibility to errors or high costs.
Machine learning (ML) methods, a branch of artificial intelligence, are increasingly being used to manage such complex production systems. This makes it possible to derive conclusions and forecasts for future processes from data obtained from sensors, for example. Constantly improving access to computing power and user-friendly software is opening up new and broader fields of application for ML technology.
For the large number of commercial vehicle manufacturers in Rhineland-Palatinate, however, tapping into the potential of ML is made more difficult by certain industry-specific characteristics. Low quantities and a high number of variants, as well as the high proportion of non-digitalized manual activities, lead to a comparatively small amount of available data. In addition, the commercial vehicle sector is strongly characterized by small and medium-sized companies, for which independent empowerment without concrete instructions often represents a high risk.
This is where the CVC Südwest's lead project "Use of artificial intelligence in commercial vehicle production" comes in. Led by the Chair of Production Engineering and Business Organization (FBK) at TU Kaiserslautern, it aims to harness the potential of ML for commercial vehicle production. Exemplary use cases are being researched and implemented together with companies. Based on this, a process model is being developed that enables the knowledge gained to be disseminated to other use cases.
"With this project, we are responding to the needs of the commercial vehicle industry and at the same time addressing the scientifically important question of how to deal with small, heterogeneous data sets in production," says Prof. Dr.-Ing. Jan C. Aurich from FBK, describing the relevance of the project.
Sponsor:
Commercial Vehicle Cluster (CVC) Südwest
European Union European Regional Development Fund - Rhineland-Palatinate
Kontakt
M. Sc. Patrick Rüdiger
E-Mail: patrick.ruediger(at)mv.uni-kl.de
Telefon: 0631 / 205 – 4282