Using data to create a better future for rail

One aim of the ‘intelligent train’ concept is to provide a single maintainer-friendly view of the train. True digital enablement involves the ability to predict failures, highlight hidden problems and issue real-time alerts when failures happen. By using information in a more structured, controlled and repeatable way to plan corrective maintenance, engineers can move towards a condition-based maintenance (CBM) regime, helping to maximise equipment life, increase availability, reliability and reduce costs. The key is to identify potential failure warning signs before a failure occurs, as the repair cost is usually typically far lower to handle pro-actively as opposed to after the failure has occurred.

Huge amounts of data

Train systems generate a huge amount of data – a standard EMU generates in excess of 5,000 signals, equivalent to 2GB of data per train per day, and gathering this data is costly – data transmission could cost thousands of pounds per train per year. We think that about 0.25 per cent of this data is critical from a maintenance perspective, so the secret is smart use of the full data set. This requires the ability to access this data, process it and then have an on-shore back office solution which can visualise and analyse it, develop predictive algorithms and integrate procedures into maintenance management. Data can then be compared to understand how fleets are performing relative to each other and, if presented in a standardised form, allow for direct comparisons across manufacturers.  A key part of the savings comes from changes in maintenance practices based on the information being generated from the CBM solution.

Reducing failures and increasing availability

An example of the success of the intelligent train concept is its application to the Portuguese railway’s fleet of Pendolino trains. Here, 70 per cent of maintenance tasks are now condition-based and in a more controlled and managed environment. This has helped reduce in-service failures by 43 per cent, increase availability by 20 per cent, raise average fleet mileage by one-third and reduce instances of ‘no fault found’ by 40 per cent. Over a 12-year period, maintenance costs have fallen by 57 per cent, demonstrating the significant room for improvement that the intelligent train concept offers.

We think CBM is hugely powerful. But it is only through the insight and intelligence of the engineers and maintainers that use it, that it becomes most effective.

The ‘connecting everything’ vision

As part of our ‘connecting everything’ vision and with the advent of Internet of Things (IoT), big data and artificial intelligence (AI), CBM is becoming an integral part of realising the intelligent train. Nomad Tech, our joint venture with EMEF and the Portuguese railways is focused on this market.

Our solutions enable sensing, collecting and delivering data about the train to the shore and this can be used for a number of purposes such as CBM and driver advisory systems, to identify energy efficiencies and in support of power electronics. We also provide consultancy on maintenance practices and how these can be improved to save money.

We’ve recently won a large contract which uses this data to improve the operational and reliability nature of trains. This is being used with a transport authority to ensure that the franchise is delivering the on the service levels and value that they have promised.