Future Laboratory Production: Digitizing production in medium-sized companies

2020-06-29 The Future Laboratory Production of the Center for Digital Innovations Lower Saxony (ZDIN) brings together industry partners and researchers for innovative modeling and optimization of manufacturing processes and production flows. As part of the joint project with five other universities in Lower Saxony, Matthias Schmidt, Professor of Production Management, is working with Kathrin Kramer to develop solutions from the context of machine learning to improve production processes.

Prof. Dr. Matthias Schmidt und Kathrin Kramer helfen mit ihrer Forschung, Produktionen in mittelständischen Unternehmen zu digitalisieren. ©Leupana/Janine Maier
Prof. Dr. Matthias Schmidt and Kathrin Kramer help with their research to digitize production processes in medium-sized companies.

The globalized industry is undergoing a profound change: companies are under great pressure to innovate. In addition, products are becoming increasingly individual. Examples can be found not only in medical technology or in the automotive industry. As a result, the technical requirements in machine manufacturing are increasing. The Center for Digital Innovations Lower Saxony would like to bring together the know-how of research and industry practice in the Future Laboratory Production in order to strengthen Lower Saxony as a business location. 

In the Future Laboratory Production, Matthias Schmidt and his research assistant Kathrin Kramer solve concrete problems from industry partners: "We are working on the question of how we can use the sometimes very heterogeneous data in companies to allow production orders to flow through production as efficiently as possible. Today there is much more data available on production processes than a few years ago. This can be used to improve future processes. To achieve this, we use various approaches from the context of machine learning," explains Schmidt. The scientists obtain the data from production systems of the participating companies. In this way, the researchers can identify problems and find solutions that will be made available to the industry at the end of the project.

In the Future Laboratory Production, technologies are being explored that enable independent optimization of manufacturing processes and production workflows. The aim is to create a continuous digital production chain. Self-learning machines can shorten processes and increase the quality of the products. "Previous methods are reaching their limits due to increasing complexity. With data-supported methods, we are trying to model influencing factors in the production processes that have not been recorded up to now in the best possible way, to recognize patterns in the data and thus plan more precise processes," explains Kathrin Kramer. For example, certain machine learning methods can be used to identify patterns in existing data on, for example, materials or working times and to learn from these for future orders. The machine can thus continuously improve its own processes as a self-learning system.

The Lower Saxony Ministry of Science and Culture are funding the research project at Leuphana University with 438,000 euros until the end of September 2024. The partners are Leibniz University Hannover, Emden/Leer University of Applied Sciences, Hannover University of Applied Sciences, Braunschweig Technical University and the OFFIS Institute.

The Institute for Product and Process Innovation invites entrepreneurs to a video conference on 22 September on the topic "What potential does machine learning have in my company?". Between 5 and 6.30 pm the practical application of machine learning in the production environment will be discussed.

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