With the contribution of the LIFE programme of the European Union - LIFE14 ENV/GR/000611 and       the co-financing of Green Fund, Greece
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DB and Siemens launched pilot to support predictive maintenance

Prediction is a useful tool for engineers and transportation companies. Rolling stock maintenance is one of the most important pillars in railways. Good fleet maintenance helps a railway company to improve the fleet availability and reduce problems in services and supply of goods.

  

 

Siemens and DB join their forces to produce intelligent algorithms and predictive analytics so to optimize fleet availability. In a 12-month pilot project a Class 407 Velaro D high speed train fleet is going to be tested.

 

Data will be received from DB fleet and data will be analysed from SIEMENS. Jochen Eickholt believes that this study is going to improve maintenance work.

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Source: Railwaygazette

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The LIFE GYM [LIFE14 ENV/GR/000611] project is co-funded by the LIFE programme, the EU financial instrument for the environment.

 

The sole responsibility for the content of this report lies with the authors. It does not necessarily reflect the opinion of the European Union. Neither the EASME nor the European Commission are responsible for any use that may be made of the information contained therein.

 

Start Date: 15 September 2015 – Duration: 35 months

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Date of last update: 18/02/2020

The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the European Union. Neither the EASME nor the European Commission are responsible for any use that may be made of the information contained therein.