Imagine a scenario where potential problems in railway systems are detected and resolved before they can disrupt operations. For railway undertakings and infrastructure managers, predictive maintenance is a powerful tool for proactive problem-solving and cost savings. By adopting predictive maintenance solutions, the potential savings in railway maintenance could reach up to EUR 7.5 billion annually.
However, achieving these benefits requires a deep understanding of the various aspects of maintenance and how they affect asset lifecycles.
Numerous projects worldwide aim to optimize maintenance costs and activities, utilizing data analytics to transform traditional approaches to railway maintenance.
Current market solutions offer insights on infrastructure, rolling stock, and signaling systems, enabling proactive measures that can significantly reduce downtimes.

Why does maintenance matter?
Electronic systems in railways, which include microprocessors, circuit designs, and complex equipment, are prone to failure, especially under demanding conditions. The lifecycle of these systems typically involves multiple stages, from initial design to final deployment. Each stage — architecture, coding, integration, and installation —introduces potential risks and errors, which can only be identified through rigorous testing at the software or hardware level.

To read more about this article and to have full access to premium content SUBSCRIBE to Basic Subscription Plan or Premium Subscription Plan.