Project PrimaVera | Hogeschool Saxion

Predictive maintenance is the ability to use data-driven analytics to optimize the upkeep of capital equipment. PrimaVera stands for Predictive maintenance for Very effective asset management.

In PrimaVera, we create value by transforming the collected data from intelligent systems into predictions about the system’s health, by avoiding future failures through just-in-time maintenance, by doing maintenance exactly when and where needed, according to the specific needs of the system and according to its specification.

Topic

Smart industry, predictive maintenance, prognostics, health monitoring, sensors, human factors

Program objectives

The vision of PrimaVera is to make deployment of predictive maintenance easier and more effective. By using a holistic approach to the maintenance workflow, the team will develop accurate, scalable, and real-time health diagnostics and prognostics and turn these into effective maintenance strategies that can operate in complex and uncertain environments. Thereby, making major steps in realizing the promises of predictive maintenance: better system performance at lower costs.

While the building blocks for predictive maintenance, such as sensor technology, data analytics, and optimization exist, key elements for the successful implementation of predictive maintenance are still missing: accurate prognostic and optimization algorithms, their scalability, and especially their integration and automation.

Partners

University of Twente (lead manager), Saxion, Eindhoven University of Technology, The Hague University, Radboud University Nijmegen, NLR, RWS, Damen, Technobis, Alfa Laval Royal NL Navy, RWS, NS, ASML, Royal IHC, Rolsch Asset Management, Waterschap De Dommel, ORTEC Consulting Group