Model railway to maintain reliability and cut costs

1 min read

A £330m programme to create a detailed digital model of the UK’s rail network is predicted to save up to £1bn over the next decade.

Now into its second year, Network Rail’s six year ORBIS project, which is being rolled out with IT consultancy CSC, will collate data on all of the network’s key assets and enable engineers to make better-informed decisions about how to operate and maintain rail infrastructure.

Programme director Steve Dyke explained that the project is a response to the huge growth in the railways and a predicted increase in passenger and freight journeys that will make it increasingly difficult to grow capacity and maintain reliability whilst keeping down the running costs.  

Dyke said: ‘To meet these challenges, we have to do things differently and technology can help us manage this conundrum by putting quality asset data at the heart of decision making.’

The system is based on the national criminal intelligence model, an effective method of turning disparate data into valuable intelligence that is now used globally by police forces to help make strategic and informed decisions. 

Dyke said that by applying this approach to the railway network it will be possible to make more informed judgements, better anticipate the knock-on effects of these decisions and move towards a predictive maintenance model where repairs and interventions can be made before problems arise.

He said all of this will help save money by reducing the huge volume of infrastructure and maintenance work that’s carried out across the network every year.

‘It’s effectively about doing less: changing less track, changing less signalling, rebuilding less bridges and civil structures, and it’s all done because I’m able to make an informed decision,’ he said.

At the heart of the project is a vast 3D map of the entire UK rail network that has been created using a combination of existing data and new data that’s been gathered by helicopter-mounted Lidar technology. 

Known as RINM (rail infrastructure network model) this technology is currently being rolled out to the network’s engineers, who can use a tablet-based Google-earth style app to access detailed information on variables such as the slope of a track to the density and shape of the trees that border it.

Dyke said that in order to keep track of environmental changes, this exhaustive survey will be refreshed every five years. He added that his team is investigating the use of drones, rather than manned helicopters, to carry out future surveys.