Staying on track

Date: 2018


  • data analytics
  • Ethnography

New approaches to rolling stock maintenance help reduce costly downtime

Partners: Hitachi Rail

New challenge

As one of the main manufacturers of the Japanese shinkansen (bullet trains), Hitachi has decades of experience designing and building high-quality rolling stock. In recent years, Hitachi Rail has begun to transition from just being a manufacturer towards business models in which it also maintains the trains. While familiar to other parts of the company’s business, such the elevator industry, this was new ground for Hitachi Rail. It also presents special challenges. Trains are complex pieces of engineering that can be expensive to maintain. Parts are difficult to replace quickly: simply changing a wheel, for example, requires an entire unit to be taken out of service, leading to costly downtime.

“Whole system” approach

With its contract for the Javelin HS1 operation in the UK, Hitachi Rail quickly gained experience in the critical field of high-quality, efficient maintenance. Techniques used included online condition monitoring (OCM), where connected components can continuously report their status, helping with the scheduling and pre-emptive repair of potential defects, and upgrades to components. However in rail, OCM alone cannot solve the problem of disruptive downtime: units still need to be taken out of service to be repaired. For a maintenance programme to be truly effective, there must be a deep understanding of the whole cycle.

So Hitachi’s European Centre for Social Innovation supported Hitachi Rail with a “whole system” approach. This combines data analytics with an understanding of how the workforce operates, how data is processed and analysed, and how decisions are made. It differs from the current emphasis throughout rail and other industries on data analytics as a whole solution.

Transforming maintenance

For example, our work included an ethnographic study to identify where engineering bottlenecks were formed, where critical asset knowledge needed to be shared and communicated, and how the operation could be improved to speed up repairs and reduce cost. We also worked with Hitachi Rail on a maintenance transformation programme. This captured use-cases for condition monitoring to pinpoint failure modes for specific components. To identify efficient maintenance regimes for different systems, we undertook a feasibility study for reliability-centred maintenance (RCM), a discipline that aims to identify all potential faults and attribute them to events using statistical analysis of historical failure records.

Capturing tacit knowledge

As we continue to help Hitachi Rail’s maintenance capability evolve in its competitive industry, the European Centre for Social Innovation is currently designing a programme to make best use of engineers’ expertise. The engineers who work in rail depots often know which elements to focus on. But this valuable tacit knowledge is often not well documented. So we look at how to capture and digitise this know-how. In essence, our approach starts from the physical knowledge of an asset – combining both human knowledge and condition monitoring – rather than simply focusing on data analysis. This hybrid approach gives results and findings greater value.

Beyond rail

Hitachi prides itself on its ability to solve a broad range of social and engineering problems with innovative technologies. The research work undertaken by the European Centre for Social Innovation is widely applicable to industries outside of rail and we are currently developing practical maintenance solutions for the automotive and heavy machinery industries.

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