PrimaVera Project is a groundbreaking initiative funded by the Dutch National Research Agenda (NWA) that aims to revolutionize asset management through predictive maintenance. By implementing predictive maintenance techniques, such as just-in-time maintenance, the project aims to enhance the reliability of critical infrastructure and production resources while significantly reducing maintenance costs.

Unlike existing predictive maintenance methods that are limited to small-scale systems and face scalability challenges, PrimaVera is developing cross-level optimization methods. These methods take into account the interconnected nature of processes within the maintenance chain, ensuring optimal sensor and measurement choices for accurate predictions and high-quality results.

Through their research efforts, PrimaVera is at the forefront of advancing maintenance planning using deep reinforcement learning, making it possible to eliminate train delays, power outages, and production machine failures. The project's latest publications reflect the breakthroughs achieved in various areas of maintenance, such as impact identification of composite plates and spare parts inventory management.

Stay informed with PrimaVera's peer-reviewed articles, factsheets, videos, and news updates to witness the transformative power of predictive maintenance in action.