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.
2021 |
| : Damage detection using in-domain and cross-domain transfer learning. In: Neural Computing and Applications, 2021. |
| : Balancing Wind and Batteries: Towards Predictive Verification of Smart Grids. In: 13th NASA Formal Methods Symposium, 2021. |
| : AlwaysSafe: Reinforcement Learning Without Safety Constraint Violations During Training. In: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pp. 1226-1235, IFAAMAS, 2021. |
| : Robust Finite-State Controllers for Uncertain POMDPs. In: 35th AAAI Conference on Artificial Intelligence, 2021. |
2020 |
| : PrimaVera: Synergising Predictive Maintenance. In: Applied Sciences, vol. 10, no. 23, 2020, ISSN: 2076-3417. |