AI-based control systems for machines, plants, and process chains
Research alliance FORinFPRO receives �2 million in funding
Over the next three years, the Bavarian research alliance “Intelligent Manufacturing Processes & Closed-Loop Production” (FORinFPRO) will be researching fundamental concepts for process-specific sensor and condition monitoring, as well as the data-based modelling, control, and optimisation of manufacturing processes. The project has been funded by the Bayerische Forschungsstiftung to the tune of around �2 million. Tobias Gotthardt, Bavarian State Secretary for Economic Affairs, Regional Development, and Energy, handed over the confirmation of funding today. FORinFPRO is a joint project of the University of Augsburg and ten other partners from research and industry. Body parts for the automotive and aerospace industries as well as other lightweight components are manufactured using innovative processes such as wet-lay production, injection moulding, and ultrasonic welding. These consist of many small individual processes and parameters such as, for example, the temperature of ovens and the running speeds of belts. How can we develop self-adaptive control systems for machines, plants, and entire process chains that due to Artificial Intelligence (AI) are able to learn from past processing steps in order to adapt to future processing requirements, thus working more efficiently? This is the central research question of the new Bavarian research alliance “Intelligent Manufacturing Processes & Closed-Loop Production” (FORinFPRO). The Bavarian State Secretary Tobias Gotthardt today presented the decision of the Bayerischen Forschungsstiftung to fund the project to the tune of around �2 million. Expressing his enthusiasm for the project, he said, “The use of AI in manufacturing in medium-sized companies as well global corporations is what we need in order to future-proof Bavaria as an industrial location. The project makes a significant contribution to our Bavarian Hightech Agenda and is therefore especially worthy of such a high rate of funding. The combination of eight research and seven industry partners is an excellent prerequisite for delivering sophisticated research capable of delivering viable economic results. ?? The FORinFPRO project has a broad scope. “We will analyse the individual processes required for the production of lightweight components, monitor them with sensors, and create digital models. This will enable us to create new interfaces between manufacturing processes and their control systems. The aim is the complex interlinking of individual processes and thus global control of the entire process,” explains Prof. Dr -Ing. Christoph Ament from the Chair of Control Engineering at the University of Augsburg and spokesperson for the project. As a concrete example, if a non-woven material, which is the starting point of many manufacturing processes for lightweight products, becomes too thick as a result of the manufacturing process, workers involved in subsequent processing steps have to adjust the processing parameters. In future, these subsequent processing steps will automatically adapt using AI algorithms and everything will be interconnected. “The research alliance is researching how AI can be implemented in order to continually learn from processing data. The end result will be a closed-loop concept with process chain capability, in which the data acquired from the process based on AI models directly influences the process itself. This should enable the development of future learning-based manufacturing processes, such as the stable processing of recycled materials in injection moulding,” explains Rupert Hirn, Teamlead Digital Applications & Data Intelligence at KraussMaffei Technologies GmbH and deputy spokesperson of the alliance. ? Alongside the resulting higher quality products, there is the advantage that AI-supported control processes may actively compensate for fluctuations in the processing of material, as for example where they include recycled materials, thereby making the process more stable. This opens up possibilities for resource efficiency if, for example, entire processes are able to react to the availability of solar power.? Prof. Dr Dr h.c. (NAS RA) Arndt Bode, President of the Bayerischen Forschungsstiftung is delighted about the funding. “This pioneering joint project is a prime example of how the Bayerischen Forschungsstiftung effectively supports the transfer of the latest technologies from science to industry. Since its founding in 1990, the foundation has funded over 1,000 projects to the tune of �644 million and together with co-financing by Bavarian industry generated a total project volume of around �1.41 billion.” University of Augsburg, Prof. Dr -Ing. Christoph Ament, Chair of Control Engineering University of Augsburg, Prof. Dr Markus Sause, Director of the AI Production Network Augsburg University of Augsburg, Prof. Dr Kay Weidenmann, Chair of Hybrid Composite Materials University of Augsburg, Prof. Dr Wolfgang Reif, Institute for Software & Systems Engineering University of Augsburg, Prof. Dr -Ing. Michael Kupke, Chair of Polymer Composites Technology University of Technology Nuremberg, Prof. Dr. Wolfram Burgard, Founding Chair Department of Engineering Fraunhofer Institute for Casting, Composite, and Processing Technology (IGCV), Augsburg Center for Lightweight Production Technology (ZLP) of the German Aerospace Center (DLR) KraussMaffei Technologies GmbH, Munich MAGMA Gie?ereitechnologie GmbH, Aachen Vallen Systeme GmbH, Wolfratshausen BCMtec GmbH – Bavarian Consulting & Measurement Technologies GmbH, Augsburg soffico GmbH, Augsburg SGL Carbon, Meitingen Bolle & Cords Elektrotechnik GmbH, Horst
The aim is to be able to globally regulate processes
Higher quality products and greater processing stability and efficiency
A pioneering joint-project
The concept developed in the joint project will also be transferred to other manufacturing processes in the future, such as those being researched by the AI Production Network at the University of Augsburg. “The FORinFPRO project is an excellent example of what the AI Production Network at the University of Augsburg and its partners want to achieve: that is, a combination of production technology and AI methods with reference to industrial application,” says Prof. Dr Andreas Rathgeber, Vice-President for Educational Success –Teaching and Studies at the University of Augsburg, summarising the project.
The AI Production Network Augsburg is an alliance of the University of Augsburg, the Fraunhofer Institute for Casting, Composite, and Processing Technology (IGCV), the Center for Lightweight Production Technology (ZLP) of the German Aerospace Center (DLR) in Augsburg, as well as the Technical University of Applied Sciences Augsburg. Regional industry partners are also involved. The aim is to conduct joint research into AI-based manufacturing technologies at the interface of materials, manufacturing technologies, data-based modelling, and digital business models. The AI Production Network Augsburg is funded to the tune of �92 million by the Bavarian State Ministry’s Hightech Agenda.
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