University of Ottawa

Published purpose

This Project involves developing an AI-based Digital Twin for heavy freight rail car operation in the railway industry. The objective is to ensure better Canadian transportation by improving safety of railway operations and reducing the cost of maintenance and down time. Digital Twin (DT) is a disruptive technology that involves creating a living model of a physical asset. The living model will continually adapt to changes in the environment or operation using real-time sensory data, which can in turn forecast the future state of the corresponding physical assets. A Digital Twin can be used to proactively identify potential issues with its real physical counterpart, which allows the prediction of the remaining useful life of the physical twin by deploying machine learning-based models (or so-called data-driven models) developed from “big data”. By performing AI-based predictive maintenance for twinned freight cars, failures or defects can be fixed before they result in potential safety issues and costly service interruptions and delays.