PrimaVera (Predictive maintenance for Very effective asset management - OPAC part)

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.

The project focuses on predictive maintenance, from installing the right sensors, through making predictions, optimizing maintenance, and implementing decision support systems in practice. We specifically focus on the maintenance optimization under limited information, spare parts inventory control under limited information, and the interaction between decision support systems and human planners