Dr. Bärbel Götz explains: "The yearly quantities in this "high mix, low volume" production range between 100 to 1,000 assemblies depending on components. Within 10 minutes there could be a change from one component to another, which would require a change in testing plans and procedures. With this project, we are pursuing end-to-end digitization of data evaluation to create transparency, flexibility, and planning reliability with complete representation - keyword digital twin - of product, manufacturing process and machine."
Prof. Dr. Kerber adds, "In order to achieve this goal, innovative solutions are needed to design test stations and to determine how loading and unloading should happen. In addition, as a basis for analysis and optimization, the existing data sources must be linked with the information from the new test stations in a new data model.”
Funding of the joint research projects
ModProFT is funded by the Bavarian Ministry of Economic Affairs, Regional Development and Energy as part of the Bavarian Collaborative Research Program in the "Digitalization" funding line - with a term of 30 months. Thus, the Bavarian Ministry of Economic Affairs is pushing the further expansion of an AI production network in Augsburg. Bavaria's Secretary of State for Economic Affairs, Roland Weigert said at the handover: "In 2020, we have launched a 100-million-euro future program for Augsburg to make the economic region even more competitive against the backdrop of structural change and technological transformation. The AI production network is the centerpiece of our growth campaign. The aim is to research the use of artificial intelligence in production processes and rapidly transfer the technology to industrial applications. To this end, we are investing a total of 92 million euros in scientific research and the profitable transfer of findings to companies."
The joint research project "ModProFT" is being supported with over 426,000 euros. The joint partners are BMK professional electronics GmbH from Augsburg and Augsburg University of Applied Sciences.
Götz emphasizes, "The aim is to prepare manufacturing processes and workflows in such a way that, among other things, fields of application such as "predictive maintenance" and "predictive quality" can be evaluated by means of artificial intelligence. In this way, we are strengthening BMK's competitive power."