Digital Twins as Enablers of Predictive Maintenance in Rail Transport Services

Rail transport services are emerging as a major sustainable transportation option.However, these services are significantly dependent on high investments and complex logistics, which creates the need to identify opportunities to minimize the waste of resources to remain affordable and competitive.The digital twin, one of the core concepts of the Industry 4.0 paradigm, represents an important support in ensuring sound decision making, as it enables detailed realtime monitoring of the state of a piece of equipment during its operation.This work seeks to explore the potential of the digital twin to support predictive maintenance processes in railway vehicles and infrastructure.Two digital twin prototypesa digital twin of a railway vehicle model, and another for a section of a railroad -were developed.Both prototypes are composed of a relational database for storing the data on the operational conditions of the equipment and a mobile application that works as a dashboard of the digital twin.The developed prototypes provide deeper knowledge of the working conditions of a vehicle, which enables predictive maintenance through the analysis of the historical evolution of the data.The results of the study also allow the identification of possible improvements and research opportunities for future work.