In recent years, the concept of “digital twins” (DTs) has gained increasing attention in the railroad industry. This complex concept allows the creation of digital representations of physical assets or processes and can support a railroad’s transportation system throughout its lifecycle. For decades, MxV Rail has used the Facility for Accelerated Service Testing (FAST (Registered trademark.) to enable research and testing designed to improve the safety, reliability, and efficiency of North American railroads. At FAST, data streams generated by 1) operations, 2) maintenance, 3) wayside and onboard detector technologies, and 4) individual testing are employed to better understand the effects of heavy axle loads (HAL) as high tonnage accumulates on track components at various stages of wear. The development and implementation of DTs have strong potential to support decision-making for infrastructure and mechanical systems with regard to monitoring, predictive maintenance, and knowledge transfer to conditions where data is unavailable. This paper seeks to open the conversation by reviewing the concept of DTs in the North American railroad industry and showing the vision of the implementation layers for making a DT for FAST and the current efforts to achieve this vision.
Digital Twin Vision for Freight Railroads: A Case Study in North America
IEEE Transactions on Intelligent Transportation Systems ; 26 , 8 ; 12740-12745
01.08.2025
828926 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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