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Cross-Industry Predictive Maintenance Optimization Platform
Period: 01.09.2017 – 01.06.2022

The CIMPLO project aims at developing a cross-industry predictive maintenance optimization platform, which addresses the real-world requirements for dynamic, scalable multiple-criteria maintenance scheduling. To achieve the full business advantages in terms of safety, time and financial savings, the CIMPLO-project combines predictive maintenance with dynamic multi-objective scheduling, such that maintenance events and the required assets can be dynamically (re-)scheduled.

CIMPLO consortium members are University of Leiden, Honda Research Institute Europe, KLM Engineering and Maintenance and Centrum voor Wiskunde en Informatica (CWI), Amsterdam. The project is carried out in cooperation
with Damen, Tata Steel, DAF Trucks and the University of Amsterdam.