Dr. Diego Galar , Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering, LTU, Luleå University
• Information extraction to assess the overall condition of the whole system. Integrating asset information during the entire lifecycle. Gaining accurate health assessment of the whole system.
• Augmenting datasets before training data-driven algorithms. For this purpose Data covering a wider range of scenarios can be obtained by synthetic data generated by physics-based models. These models need to be realistic and provide meaningful and comparable information about the behaviour of the system under observation.
• Learn how industrial AI can help the use/owner/maintainer/designer to perform a virtual commissioning of the asset where it is digitized and virtualized and produce a digital twin containing both data driven and physical information.