by Thom Badings

PrimaVera Project

No more train delays, power outages, or failure of production machines? The PrimaVera project, funded by the Dutch National Research Agenda (NWA), represents a major step towards this goal. With predictive maintenance, or just-in-time maintenance (maintenance just before a system breaks down), the reliability of infrastructure and production resources can be increased and the costs of maintenance can be reduced.

Existing predictive maintenance techniques only work for small-scale systems and are difficult to scale up. Choices made in one place in the chain have an important influence on other processes in the chain. The choice of a certain type of sensors and measurements influences the type of predictions that can be made, and therefore also the quality of the predictions. That is why cross-level optimization methods are being developed within PrimaVera.

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2025

Nubia Nale Alves da Silveira; Annemieke Angelique Meghoe; Tiedo Tinga: Quantifying the suitability and feasibility of predictive maintenance approaches. In: Computers & industrial engineering, vol. 194, iss. 110342, 2025. (Type: Journal Article | Abstract | Links | BibTeX)
Luc Stefan Keizers: Hybrid Prognostics For Predictive Maintenance. Combining Physics-Based And Data-Driven Methods To Overcome Prognostic Challenges. 2025, ISBN: 978-90-365-6574-5. (Type: PhD Thesis | Abstract | Links | BibTeX)
Thom Badings: Robust Verification of Stochastic Systems. 2025, ISSN: 2950-2772. (Type: PhD Thesis | Abstract | Links | BibTeX)
Lisandro Arturo Jimenez-Roa: Reliability and Maintenance for Engineering Systems: Fault Trees, Degradation Modelling and Maintenance Optimisation. 2025, ISBN: 978-90-365-6407-6. (Type: PhD Thesis | Abstract | Links | BibTeX)
Bram Ton; Niek Tempert; Danny Plass: Immersive visualisation of point cloud data of railway environments. In: 2024 10th International Conference on Virtual Reality (ICVR), IEEE, 2025, ISBN: 979-8-3503-6423-1. (Type: Proceedings Article | Links | BibTeX)
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