Smart maintenance systems allow train operators to detect railway faults and alert them to danger. Yet many existing systems are outdated, prioritise maintenance and are not as accurate as they could be. This often leads to false alerts, significant delays and costly repairs – not to mention potentially hazardous situations.

Today, ongoing developments in technology are delivering more accurate and efficient solutions. The Thales Smart Maintenance Platform TIRIS™ offers predictive maintenance capabilities across a number of critical railway assets including point machines. It is designed to empower users by giving them access to extensive data on their chosen railway assets, which can support their decision-making process. The implementation of advanced algorithms helps operators and maintainers to go beyond traditional, remote, condition monitoring, and uses technology such as machine learning to automatically calculate parameters such as the asset health.

TIRIS™ Points Predict brings a new advancement. Already launched into international markets, TIRIS™ Points Predict is a smart maintenance service for rail network operators. It improves accuracy and alert detection by monitoring trackside equipment and learning performance norms.

Whereas current systems tend to work by “discovering” – enabling analysis/ad-hoc investigation into large volumes of data – TIRIS™ Points Predict’s algorithms introduce a “prediction” functionality (as the name suggests). By applying machine learning algorithms to multiple data streams, it automates diagnosis and prognosis of asset behaviour. The results generated by these ‘Predict’ solutions can be incorporated into alarm management systems to notify operators to high priority events. The system can also automate the raising of work orders against defective assets, for example – saving operators’ time.

Thus TIRIS™ Points Predict facilitates a more efficient and higher quality rail transport service by delivering a more intelligent, predictive fault monitoring and classification system. The result is: 

• fewer passenger delays and cancellations (due to less equipment failures)
• decreased risk of fines from rail regulators (for delays)
• less trackside work which in turn reduces the risk of worker injury
• no constant need for asset expertise and complex data interpretation
• operations staff are released from repetitive monitoring work to focus on other tasks.

TIRIS™ Points Predict is now being rolled out to new customers and geographies, building on success in international markets. TIRIS™ Points Predict offers a flexible solution, driven by the needs of the end customer. Plus, it is continuously evolving and is seamless to roll-out.

Thales offers Points Predict in two different ways. If there are no condition monitoring systems in place already, we can provide a turnkey solution through our software model. This means getting up and running almost immediately. If a system does already exist then we can integrate into that existing system and apply this new algorithm to the existing data.

If you want to learn more, come and see us at the Innotrans event, get in touch on social media or via email at: tiris@uk.thalesgroup.com.

Points Predict Features

Operating efficiencies and visible improvements to rail services include:

• Advanced Anomaly detection
• Fault classification
• Historical feature analysis – which examines changes in point behaviour over extended time periods
• Fault symptom library – supports the maintainer in assessing emerging faults
• Estimated asset life remaining
• Automatic fault identification