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March 2016: Siemens' Forecasting Model for Data-Driven Rail Systems

Wednesday, March 30, 2016

March 2016: Siemens' Forecasting Model for Data-Driven Rail Systems

When was the last time you experienced inconvenient train delays? Do you wish that railway companies could do a better job of predicting when breakdowns will occur?

Whereas in the past, maintenance traditionally consisted of checking rail vehicles at designated operating centers on a regular basis to resolve obvious problems and maintain machines, digital technologies are opening the door to a new level of service.

Siemens' Allach locomotive plant on the outskirts of Munich is a high-tech hub for train-related data analysis, which has been using special algorithms to predict when potential breakdowns may occur. Since 2014, it has been home to Siemens' Mobility Data Services Center (MDS) where experts have been working hand-in-hand with the facility's Rail Service Center to translate complex streams of mobility-related data into optimized operations.

The data streams from locomotives, high-speed trains, and local trains from Europe and other non-European countries converge at the MDS Center. By drawing upon this data, the organization's 20 programmers, database experts, and implementation managers have developed a data-driven service offering that is unrivaled in the rail sector in terms of real-time train monitoring, forecasting of wear and tear and failure of components, and analysis of complex vehicle problems.

The result: Before a rail vehicle rolls into Siemens' Service Center, its technicians already know what needs to be done, thus keeping the maximum number of trains available for use.

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Source & Image: Siemens