The PrimaVera Project aims to eliminate train delays, power outages, and production machine failures through predictive maintenance funded by the Dutch National Research Agenda (NWA). This innovative approach ensures maintenance just before system breakdowns, increasing infrastructure and production resource reliability while reducing maintenance costs. PrimaVera focuses on developing cross-level optimization methods to scale up existing predictive maintenance techniques for more effective and high-quality predictions.
The PrimaVera project comprises six technical work packages and two dedicated to dissemination and management. Effective communication and management across the chain are vital aspects of this initiative. The consortium comprises 13 partners, including six academic and ten industrial or societal collaborators.
Our team from the University of Twente is primarily involved in work package 5 in collaboration with the Technical University of Eindhoven. The main objective of WP5 is to gain a fundamental understanding of user requirements and design principles for creating efficient decision support tools in predictive maintenance. These insights will be utilized to design user-centered maintenance tools that enhance the effectiveness and efficiency of user-system interaction. Moreover, WP5 will develop new procedures to ensure seamless integration of data-driven maintenance systems into organizations' overall business processes, as merely developing advanced maintenance techniques without integration can render them ineffective.
University of Twente Team
