Predictive Maintenance Model for Strukton Rail

BACKGROUND INFO

Strukton Rail provides cross-border solutions in the fields of rail infrastructure, railway vehicles, and mobility systems. With a passion for technology, they focus on rail and civil engineering-related projects. Their goal is to achieve optimal availability, reliability, safety, and measurability of the rail system.

In 2015, Strukton Rail and Anchormen successfully completed a pilot project in order to realize a model that can predict point failures along the railway tracks.


THE CHALLENGE

A lot of intricate work goes into developing a railway system and the infrastructure surrounding it. The goal of the joint project was to develop a model that can effectively predict rail track failure, so that maintenance can be planned and doesn’t affect daily traffic. As reactive maintenance costs resources and more importantly a lot of time, a proactive approach needs to be applied in order to avoid vehicle delays.


THE SOLUTION

The solution developed by Anchormen employs big data and A.I for predictive maintenance, based on current, temperature, and pressure. Moreover, the advanced video analysis and smart algorithms put in place allow Strukton to detect rail track anomalies. All of this permits the company to identify possible railway failure well in advance, thus maintenance can be scheduled in a way that doesn’t affect planned traffic.