EuroFMX: AI for the Next Generation of Manufacturing
EuroFMX develops industrial GenAI models for future manufacturing. HWR Berlin contributes expertise in logistics, supply chain management, and simulation-based AI.
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- Project
EuroFMX
- Laufzeit
01. Juni 2026 bis 31. Mai 2030
- HWR Berlin
Department of Business and Economics
- Projektverantwortlich
Prof. Dr. Dmitry Ivanov
- Project members from the HWR Berlin
Phu Nguyen
- Project partner
EuroFMX brings together 70+ partners from academia, research institutes, and industry across 20+ European countries. The consortium is coordinated by Politecnico di Milano and includes leading academic and research institutions such as Fraunhofer Gesellschaft, TU Eindhoven, Imperial College London, KU Leuven, and Chalmers University, as well as major industry players including Siemens, Schneider Electric, Bosch, Philips, Leonardo, Celonis, and Comau, among others. HWR Berlin participates as a research partner.
- Funded by
European Union
What is it about?
European manufacturing lacks industrial GenAI models tailored to manufacturing physics and production, relying on generic AI amid supply-chain shocks, skills gaps, and weak robotics integration
What motivates you to conduct this research?
Europe's manufacturing sector faces urgent challenges in achieving its green/digital transitions. Without foundational AI capabilities built on European values and data sovereignty, Europe risks falling irreversibly behind in industrial AI, particularly for SMEs who lack access to advanced, industry-grade AI tools.
What is the starting point?
Current Industry 4.0 systems are reactive and siloed. Only 12% of industrial robots leverage GenAI for autonomous decision-making, and 83% of European manufacturers report suboptimal GenAI performance in core tasks such as quality control and predictive maintenance. Sensitive production data processed through foreign cloud infrastructures exposes proprietary know-how, and discrete event-driven manufacturing environments remain significantly underserved by existing AI approaches.
What are the specific goals of this project?
EuroFMX aims to develop: (1) industrial-native multimodal foundation model built on manufacturing physics, materials behaviour, and production semantics; (2) a self-evolving Agentic Manufacturing Intelligence infrastructure for autonomous, continuous production optimisation; and (3) an open, SME-friendly European platform for testing, experimentation, and sandboxing — fully compliant with the EU AI Act.
How does the project team intend to achieve these goals??
HWR Berlin contributes its strong expertise in supply chain management, operations management, logistics, and AI-driven decision-making. A particular focus is placed on simulation-based methods, including digital twins and discrete-event simulation, to model, analyse, and optimise complex supply chain and production systems. HWR Berlin will leverage its proven track record in bridging academic research and industrial application, translating advanced AI and simulation models into practical, deployable solutions for manufacturing companies. This includes developing AI-supported tools for dynamic supply chain reconfiguration, resilience assessment, and autonomous logistics planning that directly address real-world industrial constraints.
Contact
Department of Business and Economics
Prof. Dr. Dmitry Ivanov, Professor für Supply Chain Management
dmitry.ivanov(at)hwr-berlin.de