Life 4.0 Trains – Smart, Green and Integrated Transport

Life 4.0 Trains integrates validated innovative technologies and solutions while upholding the strictest safety and security standards in the railway industry.

Contributes to the achievement of the Single European Railway Area, by helping provide a faster and less costly transition to a more attractive, user-friendly (including for persons with reduced mobility), globally competitive, efficient and sustainable European rail industry.

Life 4.0 Trains contributes towards a reduction of the life-cycle cost of the railway transport system, through a reduction of the costs of developing, maintaining and operating the rolling stock, as well as increasing the life span of material, reliability and punctuality of rail services.

Life 4.0 Trains pushes digitalisation, enabling legacy vehicles to provide diagnostic data that can be used for Condition-Based Maintenance (CBM), without the need for installing additional sensors. SmartTrain reduces maintenance costs and increases components reliability and life span. It gathers huge volumes of heterogeneous data that can be used to predict the effective need of maintenance activities, required to prevent component failures, by using big data and analytics methodologies and techniques.

Life 4.0 Trains encompasses a train monitoring system, designed to perform smart metering and asset management of railway systems. It collects data regarding locomotive and rolling-stock technical parameters directly from the internal communication lines. The knowledge generated from the analysis of these parameters is precious for life cycle management and intelligent asset maintenance planning. It includes automatic detection of anomalies, embodying the maintenance workflow processes and it implements predictive models of decaying infrastructural assets. In short it enables the implementation of:

  • Maintenance strategies, for faults prevention (i.e. early detection) and troubleshooting;
  • Asset Management strategies, for adapting and optimising maintenance activities to diverse clusters of similar assets.