INTELLIGENT ASSET MANAGEMENT
Fixing assets before they fail
Finding ways to reduce in-service asset failures is a priority for rail businesses everywhere. The failure of a single item of equipment – such as a point motor or a track circuit – can cause chaos, triggering delays and discontent for passengers and freight customers.
Service disruptions caused by equipment breakdowns can result in heavy penalties for infrastructure managers and train operators. On top of this, there’s the high cost of putting things right afterwards: repairing equipment following a failure is considerably more expensive than carrying out remedial work before it goes wrong.
Monitor any asset
Thales’ Intelligent Asset Management (IAM) is an enterprise-grade remote condition monitoring solution that pinpoints potential problems and raises the alarm before assets fail.
This solution is capable of monitoring all assets
information collected through
intelligent asset monitoring assists
the move to proactive
The solution – already in use throughout the UK main line network – also supports incident resolution and provides new insights into long-term asset performance.
IAM works by continuously monitoring key assets – such as points, point heaters, signalling power supplies and track circuits – and comparing their actual performance with calibrated behavioural norms. The system also identifies trending behaviours – incremental changes that could indicate future problems. These tell-tale diagnostics allow maintenance teams to act before assets fail.
While remote condition monitoring systems have been in existence for a number of years, Thales’ IAM approach offers a number of important enhancements for rail customers – one of which is the ability to monitor any asset type in near real time.
“This solution is capable of monitoring all assets, irrespective of the manufacturer,” says David Taylor, Business Development Director, Thales UK. “That’s important, because many infrastructure businesses now have to deal with a multitude of different monitoring systems from different suppliers. What we are providing is a single enterprise-level solution with a single user interface.”
As well as reducing delays, IAM delivers a number of strategic benefits. One of these is maintenance optimisation. Better information about assets supports the shift to predictive maintenance strategies, with resource targeting based on real needs. IAM also measures the effect of maintenance interventions, so operators can continuously improve procedures.
Historical analysis of data generated by IAM offers deeper insights into the long-term performance of assets, so operators can easily
assess the reliability of equipment produced by different manufacturers. This can be fed back into procurement decisions for asset renewal.
“The enterprise-wide information collected through intelligent asset monitoring assists the move to proactive maintenance regimes,” says Dr Stephen Ayers, IAM Business Manager, Thales UK. “The condition of key assets can be monitored in near real time by authorised users allowing timely and appropriate action to be taken.”
Enterprise asset management
Thales’ IAM uses commercial off-the-shelf hardware and software, so there’s no supplier tie-in. And unlike proprietary remote condition monitoring systems, Thales’ IAM is non-intrusive: monitored assets require no internal modification.
This makes it easy and cost-effective to bring new assets into the system – including mobile ones. “The architectural and technological approach we take is capable of monitoring both fixed infrastructure and trains,” says Mr Taylor. “This opens up the prospect of being able to identify track-related problems with an even greater degree of precision.”
|INTELLIGENT ASSET MANAGEMENT AT A GLANCE|
• Flexible – monitors any asset from any manufacturer
• Scalable – by route, region or country
• Optimise maintenance – with targeted interventions
• Service proven – deployed throughout the UK rail network
• Open system – uses off-the-shelf hardware and software
• Easy to use – single interface for optimum user familiarity