Smart Point Machine

Adaptive monitoring and diagnostics catalystProblem description

Railway operators often face unexpected point machine failures that lead to costly downtime and unplanned repairs. Without early insights into abnormal states, maintenance teams must react after the failure has already happened. This means they may not have the right tools or parts available and cannot prepare effectively. As a result, repairs take longer, costs rise, and the reliability of rail operations suffers.

Enabling failures detectionOur Solution

The Smart Point Machine continuously monitors the condition of point machines using high-performance sensors that capture real-time data. Analysis provides clear indicators and generates instant alarms when anomalies occur. The system can be programmed remotely and integrated with SCADA, signaling, or SIEM systems. Scalable to various models, it enables condition-based maintenance that prevents breakdowns and reduces service interruptions.

How it works

For each phase of the switch operation indicators are calculated by off-loaded post-processing from the acquired data.

Alarm settings on the calculated indicators on each point machine.

Field data acquisition equipment (current, voltage, active power), inte-grated into the railway system, with no impact on safety, meeting its con-straints, and proven.

Highly flexible deployment architecture of the SPM solution, “Egde com-puting”, “Cloud” hosting or “On premise”.

Hot swapping of equipment.

Cybersecurity is handled by design.

Hardware

Continuous and real time based on acquisition device, sensors, data concentrator and server application
Data acquisition on track and/or in signaling room
Real-time monitoring
CE compliant
EMC compliant with : EN 50121-4, EN 61000-6-2, EN 61000-6-4

New Whitepaper Available From Monitoring to Predictive Maintenance

Railway operators generate valuable turnout and switch machine data every day. Yet in many cases, this information is only used to indicate whether a switching operation was successful or not. What if the same data could provide deeper insights into asset health, degradation trends and future maintenance needs?

Together, Vossloh and AI analytics specialist Predge have developed an approach that transforms existing movement and operating data into actionable maintenance intelligence. By combining Vossloh’s extensive railway infrastructure expertise with Predge’s advanced analytics capabilities, operators can identify changing asset conditions earlier, prioritize maintenance activities more effectively and reduce the risk of unplanned failures.

Our latest whitepaper explains how condition indicators, anomaly detection and predictive analytics can be applied to turnout and switch machine data, creating a foundation for condition-based maintenance and smarter operational decisions. The paper also provides practical examples, outlines the associated business benefits and demonstrates how existing data can be leveraged before investing in additional monitoring hardware.

Can your turnout data predict future failures?

Request whitepaper today!

Learn how railway operators can use existing turnout and switch machine data to identify degradation earlier, reduce unplanned failures, and prioritize maintenance based on actual asset condition instead of fixed schedules.

Stefan Distlberger

Head of Business Development Digitalization

WhitepaperOverview and data sheet

Smart Point Machine Data Sheet