Predictive maintenance is a key IoT use case that’s improving railroad operations

At a high level, the internet of things (IoT) is all about maximizing asset availability, reliability and efficiency. This is highlighted in the railroad industry, both passenger and cargo, where timelines has a direct impact on business profitability. Here we examine two case studies wherein railroad operators leveraged IoT and related solutions to detect problems before they occurred in an effort to optimize operational efficiency.

Deutsche Bahn in Germany

Deutsche Bahn aims to implement predictive maintenance tools to be able to control its points.To enable that, the current pulse at the connection cable to the point is measured in the signal box. Special sensors also record status data, which is then analyzed centrally, at relevant parts of the point controller. Possible deviations from the reference value, such as occur before faults arise, are detected by smart systems at an early stage. Once this occurs, service teams can then inspect the affected parts more closely on site and  replace them if necessary so that operations are not disrupted.