Access to data is a critical point to implement advanced maintenance processes in the factory of the future. The needed interoperability faces different issues and particularly concerning semantic modeling. The need to gather domain experts, data scientists, advanced computer science experts, modeling experts is one of the challenges to succeed.

Maintenance will also play a significant role in the implementation of digital twins bringing together data from models, especially behavioral models, with data from sensors on equipment in operation or historical maintenance data.

Various means need to be experimented to improve interoperability in the real world of the production systems and plants in industry: shared terminology, model-based systems maintenance, big data analysis thanks to IA algorithms, ontologies, …

The purpose of the workshop is to share outcomes of projects implementing these means, to identify results and open points in order to define the building blocks of the maintenance of the future.