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(RSM)Rail Digital Twins For Rolling Stock Maintenance Analytics: An Industrial AI approach
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.

Sep 23, 2020 11:00 AM in Eastern Time (US and Canada)

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