How big data helps keep trains running on time

Siemens – the largest engineering company in Europe – is trying to improve punctuality on Germany’s rail network by utilising big data analysis and predictive maintenance.

The most recent data from the European Commission reveals that just over three-quarters (78.3 per cent) of the country’s long distance trains arrived on time. The report, published in 2014, found that just two other countries racked up worse averages, with Portugal and Lithuania coming in behind.

But it is hoped that the introduction of big data analytics will change this, the Financial Times reports. A group of Siemens employees have fitted hundreds of sensors to the trains, which relay data back to the engineers about the condition of the locomotive’s parts.

By combining two industrial disciplines – big data and predictive maintenance – the firm is able to find out what needs to be repaired or replaced before any delays are caused. This means that punctuality could be pumped back into Germany’s rail network, helping it climb the ranks and keep commuters happy.

So far, this experiment has seen all but one of the 2,300 journeys monitored by Siemens in Spain arrive less than five minutes late. This has pushed up the punctuality rate from 89.9 per cent up to 99.98 per cent, beating leader Finland’s score of 95.4 per cent.

This is not a new idea for Siemens, as it realised back in 2014 that the Internet of Things could help it provide customers with more than just hardware, as it paired together sensors and connected devices.

From there, the company decided to move its train manufacturing site from Allach to outside Munich to a digital hub. Here a group of specialists analyse the data that is generated by the sensors on the trains being monitored by the firm.

The group is looking out for patterns or anomalies that could point to an issue onboard one of its fleet. If something does need to be replaced, the specialists make sure it is done during regular maintenance checks, rather than cause a disruption to regular services.  

Renfe – the Spanish rail network that has partnered with Siemens – is so confident that the system works that it is offering commuters a refund if the service between Madrid and Barcelona is late by more than 15 minutes.

Gerhard Kress, head of Siemens' Mobility Data Services Centre, believes that the most important thing for rail networks is to avoid breakdowns, as just one can have a ripple effect and cause several services to then be delayed.
Mr Kress believes that his team has got the knowhow to make big data work hard to keep the trains running on time. He added: “We are essentially building on the know-how that Siemens has developed over the years for other types of applications, namely in healthcare and gas turbine operations.

“We have also massively invested in building our team. All our scientists not only have PhDs in data science, machine learning or mathematics, but also a background in mechanical engineering.”

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