IAM4RAIL – Holistic and Integrated Asset Management for Europe’s RAIL System
Europe’s Rail Flagship Project 3
IAM4RAIL – Holistic and Integrated Asset Management for Europe’s RAIL System
IAM4RAIL aims to establish the next generation of intelligent, integrated asset management for Europe’s rail infrastructure. Through AI-supported condition monitoring and digital twins, it reduces lifecycle costs, minimises downtime and enhances safety in the long term.
The FP3-IAM4RAIL project comprises seven integrated demonstrators for rail infrastructure that are pioneering in terms of research and innovation in the rail transport sector. The focus is on integrating condition data from advanced monitoring systems into decision-support tools and traffic management systems. Through the use of artificial intelligence and digital twins, the project adopts a holistic, interoperable and cross-border approach at European level. In addition, technologies such as robotics and additive manufacturing are being investigated with a view to sustainably optimising asset management in the railway sector.
Simplified bayesian network for holistic condition monitoring of switches (source: https://link.springer.com/chapter/10.1007/978-3-032-04774-8_78/figures/2)
With a total of 93 project participants, FP3-IAM4RAIL aims to establish the next generation of intelligent, integrated asset management for Europe’s rail infrastructure. Through innovative solutions for fixed assets and rolling stock, lifecycle costs are minimized and the service life of the infrastructure is extended. At the same time, the highest safety standards are ensured, and the reliability, availability, and maintainability of the entire rail system are enhanced.
The DLR contributes to the project through research on embedded track-side and on-board condition monitoring systems, AI methods for holistic condition monitoring, digital twins, and federated data spaces.
Disclaimer: Funded by the European Union. Views and opinion expressed are however those of the author only and do not necessarily reflect those of the European Union or Europe’s Rail Joint Undertaking. Neither the European Union nor the granting authority can be held responsible for them. The project FP3-IAM4Rail is supported by the Europe's Rail Joint Undertaking and its members.
Jahan, Kanwal und Heusel, Judith und Baasch, Benjamin und Roth, Michael und Shankar, Sangeetha und Groos, Jörn Christoffer (2026) Intelligent Shunter Locomotives for Supporting Maintenance in Industrial Railway Networks. In: Lecture Notes in Mechanical Engineering, Seiten 765-778. Springer. 8th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2025, 2025-05-13 - 2025-05-15, Luleå, Schweden. doi: 10.1007/978-3-032-03725-1_54. ISBN 978-303038076-2. ISSN 2195-4356. Volltext nicht frei.
Samson, Henk und Tiecken, Jacques und Neumann, Thorsten und Baasch, Benjamin und Camacho de Miguel, Javier und Rodriguez-Arana, Borja und Alvarado, Unai (2025) Agile Multi-Sensor Platform Leonardo: Evaluation of new Monitoring Technologies in an Operational Environment. In: Transport Transitions: Advancing Sustainable and Inclusive Mobility, Proceedings of the 10th TRA Conference, 2024, Seiten 636-643. Transport Research Arena 2024, 2024-04-15 - 2024-04-18, Dublin, Ireland. doi: 10.1007/978-3-032-04774-8_92. ISBN 78-3-031-85577-1. ISSN 2196-5544.
