ºÚÁϸ£ÀûÍø

The European research proposal euroFMX has been awarded €45 million in funding following an evaluation with excellent scores. Eindhoven University of Technology is one of the largest partners in the consortium and will receive €900,000. Within ºÚÁϸ£ÀûÍø, the project brings together researchers from the Department of Mathematics and Computer Science, the Department of Electrical Engineering, and the Department of Industrial Engineering and Innovation Sciences. This project is lead by Dirk Fahland and from the Process Analytics cluster of M&CS, Ivo Adan from with the Operations, Planning, Accounting and Control Group (OPAC) of IE&IS and Thijs van de Laar from the Bayesian Intelligent Autonomous Systems lab of EE.

Strengthening Europe’s leadership in AI

Research on core learning and analysis techniques, including incremental and frugal collaborative approaches, and on next generation smart robotic systems, is central to maintaining Europe’s position at the forefront of Artificial Intelligence. AI also plays a key role in safeguarding the competitiveness and strategic autonomy of the European scientific sector.

The project contributes to the European Apply AI Strategy, which aims to position Europe as a global leader in the development and adoption of AI. In particular, euroFMX supports the Generative AI topics within this strategy and contributes to the GenAI4EU initiative included in the AI Innovation Package of 24 January 2024. By aligning with these initiatives, the project forms part of a coordinated European approach to AI development and deployment.

Within this project, the Process Analytics cluster of the Department of Mathematics and Computer Science contributes decades of world leading expertise in process mining, providing AI systems in manufacturing with the operational context required for informed decision making and optimisation. This enables manufacturing AI to actively explore, formulate hypotheses, and self correct in real time. At the same time, the foundational research carried out within Process Analytics opens new perspectives for process intelligence across a broad range of application domains.

The manufacturing expertise in the research group Operations, Planning, Accounting and Control (OPAC) of the department IE&IS will provide a unique playground at the Brainport Industry Campus, where the AI systems developed in this project can be implemented, tested and validated on a Festo demo line. 

At BIASlab we develop intelligent agents that actively learn from and adapt to their environment. By reasoning with uncertainty, agents can actively explore, validate and align their models with observations. This active inference approach to agency presents a first-principles theory about how agents act and adapt under uncertainty. In manufacturing, real-time adaptation to disturbances and uncertainty is crucial to the efficiency and effectiveness of the manufacturing process. In this project we aim to demonstrate how active inference may enhance decision-making in a complex manufacturing context.

A new paradigm for manufacturing

Europe’s manufacturing industry faces increasing global competition, skills shortages, supply chain vulnerabilities, and regulatory pressure. euroFMX responds to these challenges by establishing a European ecosystem of Generative AI and Autonomisation Frontier Models designed for manufacturing. The aim is to reinforce Europe’s competitiveness and strategic autonomy in the digital age through trustworthy, sovereign and human centric AI for industry.

The project is structured around four strategic pillars:

• Pillar I develops Industrial AI that acts autonomously, systemically and at scale, setting a path towards manufacturing oriented Artificial General Intelligence.
• Pillar II focuses on strengthening the future workforce by bridging AI talent and industrial expertise through large scale skilling, co creation and open knowledge communities.
• Pillar III supports European digital and AI sovereignty through industrial grade, privacy preserving data spaces and HPC based AI factories, broadening access to advanced resources.
• Pillar IV advances frontier Generative AI models for manufacturing, including physics informed graph neural networks, multimodal reasoning and agentic orchestration platforms for trustworthy, interpretable and regulation ready deployment.

The project will validate its developments through high impact pilots in machining, robotics, automotive, circular manufacturing and human AI collaboration.