Smart infrastructure

Maintenance in the cloud

Predictive maintenance is essential in the race to improve efficiency and minimise delays on metros

Defective assets are a major cause of hold-ups on metro networks. Critical front-line equipment, such as point machines, axle counters, track and signalling systems, are all potential points of operational interruption.

Thales’s new predictive maintenance service for metro operators is designed to combat in-service asset failures. Delivered as a cloud service, it predicts when problems will occur – days or weeks before failure – and then prescribes corrective action.

Adopting predictive maintenance yields a number of key benefits:

• Enhanced reliability: predictive maintenance combats delays by minimising interruptions caused by equipment failure. It also helps to tackle reactionary delays – cascading holds-ups triggered by a single incident. Reactionary delays can paralyse a line or even a network. Rising congestion means they are a growing problem.
• Improved asset performance: predictive maintenance protects critical assets. Early intervention offers the chance to fix before failure. This helps to extend the useful life of assets and improve ROI by eliminating the need to replace otherwise serviceable equipment.
• Cost-effective maintenance:  smarter maintenance allows operators to make the transition from reactive to predictive maintenance regimes. This has the potential to reduce costs and improve the availability of networks.

How does it work?

Thales’s predictive maintenance service works by tapping into data generated by assets. This is monitored live and constantly benchmarked against optimal performance profiles.

When data received from an asset – such as a point machine – deviates from the norm, alarms and recommended actions are generated automatically. The system is capable of detecting tiny changes in performance – tell-tale signs of problems to come.

The beauty of the system is that the accuracy of predictions improves as data is accumulated through its self-learning components. And because Thales has data profiles stretching back 30 years, the insights offered to each customer are based not only on their own asset records, but also a wealth of historical data.

Thales’s predictive maintenance is delivered as a service via a secure cloud platform and no capital expenditure is required. Visualisations, predictions and recommendations can be accessed by any device – PC, tablet or smartphone.