Rethinking Production Management with AI

Making industrial production management in circular value chains resource-efficient yet profitable is a particular focus of Florian Stamer’s research. His goal is to use artificial intelligence to enable end-to-end, data-driven decision support—from production planning through manufacturing and quality assurance to the remanufacturing of products. This objective ties together the three main areas of his research:

In the field of production networks, Florian Stamer is researching how AI can be used to dynamically optimize complex planning and control decisions. In his dissertation and subsequent publications, he developed methods based on reinforcement learning that adjust delivery times and prices depending on demand and production capacity utilization. This allows for better alignment between customer requirements and available production capacity. Another area of focus is data-driven production planning and control, particularly for high-variety products and in circular value chains.

In the field of production systems, he investigates how digital twins, simulations, and AI methods can help make production processes transparent and adaptable. For example, he is researching how digital factory twins can be used to generate synthetic training data to automatically monitor production systems even when data availability is limited. In addition, he is developing approaches for intelligent production planning and control that can respond to changing production conditions and disruptions. The goal is to create cognitive production systems that can increasingly prepare complex decisions on their own, thereby supporting employees in managing production.

In the field of quality management, Florian Stamer develops AI-based methods for reliable and resource-efficient quality assurance. A key focus is on the intelligent combination of different inspection methods and the data-driven optimization of inspection decisions. For example, he is researching the use of reinforcement learning to selectively choose inspection steps and make the reuse of electronic components more cost-effective. In the VisInspecLLM research project, he is collaborating with industry partners to develop AI-supported solutions for automated inspection in remanufacturing. Another focus is the reliability of AI-based quality predictions, particularly through the quantification of model uncertainties. The goal is to make AI methods usable even for demanding industrial measurement and testing tasks.

Florian Stamer has now been honored as “an exceptionally successful young scientist,” according to Prof. Jürgen Fleischer, president of the WGP and director of the wbk Institute for Production Engineering at the Karlsruhe Institute of Technology (KIT), for his innovative spirit in applying the latest technologies to sustainable production.

Each year, the Scientific Society for Production Engineering (WGP) awards the Otto Kienzle Commemorative Medal to outstanding young scientists, thereby recognizing exceptional scientific achievements and individuals in the field of production engineering.

Prof. Dr. Florian Stamer has been a professor of production management at the Leuphana Institute for Production Technology and Systems since July 2025. In 2017, he first earned his master’s degree (M.Sc.) in Industrial Engineering with a focus on Mechanical Engineering from RWTH Aachen University, before taking a position as a research assistant at the Institute for Production Engineering (wbk) at the Karlsruhe Institute of Technology (KIT). Concurrent with the completion of his doctoral degree in 2022, he was appointed Senior Engineer at the wbk in Karlsruhe and took over as head of the “Quality Assurance” group. Since 2023, he has been a Research Affiliate at the International Academy for Production Engineering (CIRP). At the same time, he became a junior research group leader at the Institute for Production Engineering (wbk) at KIT before being appointed to Leuphana in 2025.