Industrial AI / eMaintenance

The overarching objective of the Industrial AI / eMaintenance R&I program is to: a) conduct a multi-disciplinary applied research in maintenance analytics; b) develop and provide an appropriate education platform in eMaintenance; c) establish an innovation process which supports implementation of research outcomes to real-world solutions. 

Industrial AI / eMaintenance focuses on topics which reflect issues and challenges within industry and academia.
Some of these topics are: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), eXplainable AI (XAI), service-oriented and event-oriented approaches, digitalisation, IoT and IIoT, Big Data Analytics, cloud-computing, distributed computing, crowd-computing, information logistics, data integration, data fusion, data processing, data visualisation, and context adaptation.

The program also aims to design, develop, and provide artefacts based on edge technology to demonstrate proof-of-concept within the aforementioned topics. The main objective of these demonstrators are to validate academic outcome in industrial contexts.