HomeDigital RailwayHitachi Rail's approach to the Digital Railway

Hitachi Rail’s approach to the Digital Railway

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Digital affects almost every facet of UK rail activity. It has been transforming rolling stock, maintenance, and passengers’ journeys for almost a decade. Industry requirements, such as ASDO (Automatic Selective Door Operation), remote CCTV and timetabling, mean that it is now impossible NOT to have a digital train.

The pace of change is now faster than ever. Train components that improve the passengers’ experience, such as intelligent information screens, are driving greater technological sophistication and the further digitisation of modern trains. Digital is already playing a vital role in increasing reliability, which remains a top priority for UK passengers.

Improving reliability

One of the manufacturers at the forefront of this technological revolution is Hitachi. Its ‘Digital Brain’, which was developed specifically to cut down the hours needed for train maintenance, consists of tens of thousands of sensors throughout the train that feed back to the main computer in the driver’s cabin. On the Class 800/802 IEP trains, for example, there are over 48,000 signals – from the engine to door sensors – which provide real-time data to the driver or, remotely, to the support team.

If an issue should arise, the train’s Digital Brain identifies and processes the system data in a matter of seconds, supporting technicians and engineers in diagnosing defects and formulating a repair plan. On a manual basis, by comparison, just identifying the source of a problem can take hours.

Although the benefits of this technology are already being seen on the company’s high speed IET and Class 385 commuter trains, the greater application of this technology will come when data analytics are combined with Hitachi’s machine learning software, enabling engineers to predict and take steps to fix potential faults before they even occur.

For every mile that Hitachi trains accumulate, more and more valuable data is gathered about their performance and general wear and tear. This establishes a data model that will start to identify trends as the fleet matures.

The machine learning software can make recommendations on when parts of the trains should be investigated or replaced. It will also identify whether certain aspects of the trains are changing or there are anomalies – for instance, if the long-term variance of door cycles is increasing or there are gradual increases in compressor times. The software will be able to identify data patterns and recommend when preventative maintenance can take place,  increasing reliability as well as driving down costs of doing unnecessary work. Equally, it can identify if the variance is symptomatic of another fault and will then recommend when a thorough depot check should take place.

Having this critical information and the capacity to fix problems before they occur has numerous and wide-ranging benefits to fleet management, ordering supplies and organising maintenance regimes. Most importantly, this all adds up to ensuring reliability remains high across the fleet’s life cycle.


Being part of a global company, Hitachi Rail is in the fortunate position that it collaborates with other companies in the group, including Hitachi Consulting, Vantara and CSI Research Labs, which specialise in big data, machine learning and Artificial Intelligence. Indeed, the global leading research company, Gartner, recently placed Hitachi in the top three “Magic Quadrant” for IoT (the Internet of Things).

Being able to call upon this leading expertise to develop, and continuously refine, the preventative maintenance product, by combining expertise in rail engineering and information technology (IT), has proved essential to creating a product that is not only effective today, but also has the potential to deliver more in the future.

To create future-proofed products, one must think ahead to predict the solutions that will add value to customers, as well as what rail passengers want to see from their trains. An excellent example of predicting, rather than simply following, demand is the work undertaken by Toyota in the automotive industry to develop in-car GPS before it was widely used by the public or before smartphones even became commonly available.

This begs the question what’s next for digital rail? Driver monitoring that ensures drivers have seen the signals, perhaps?

To ensure that Hitachi trains are future-proofed and are ‘digital ready’, they are already compatible with digital signalling, future traffic management systems and smart ticketing, even if all of this technology is not currently being fully utilised and may not have been in the original design scope.

Onboard CCTV is a good example. When it was first installed, CCTV was used to review past events. Now it provides live footage that can be accessed remotely. In the future, it may be able to identify real-time developments that can be used to warn the driver. Through incremental change and integrating new digital solutions, CCTVs functionality continues to evolve.

As in mechanical engineering, digital also goes through an iterative process of improvement. There are very few instances where installing or introducing new digital technology has worked perfectly first time. The good news is that incremental improvements to digital solutions tend to happen far more quickly than when building a complex mechanical device, such as an internal combustion engine.

The next step in the process to hone and improve the railway of the future is through sharing data. Data is knowledge, and knowledge is, most definitely, power. Sharing knowledge is how the digital railway will become a reality. Having data sets – of trains, operators and the rail network – communicating with each other is essential in achieving more trains running closer together and increasing service frequency on the current network.

Understandably, and rightly, businesses are protective of their data. Nevertheless, Hitachi Rail has already found that, where it is appropriate and legitimate to do so, pooling data provides benefits. Sharing data with suppliers about their products and their performance, and providing detailed feedback, allows them to understand where wear and tear takes place. This information can be used to adapt and improve their manufacturing accordingly. Likewise, their data is incorporated into Hitachi’s ‘data model’ and algorithms to improve predictive maintenance.

Digital workforce

As trains become increasingly digital, the workforce needs to keep up with the latest developments. IT specialists and data scientists are now at the heart of every aspect of rolling stock, from design, maintenance and operations. They regularly work alongside mechanical engineers to maintain and improve train fleets.

Data scientists have a key role to play in analysing the mountains of data created by the train’s ‘digital brain’. Hitachi’s software is able to make sense of all of this information and to turn it into easily understandable and actionable content so that maintenance teams can be as effective and efficient as possible.

Having mechanical engineers and data sciences working together is now fundamental to maintenance operations. Transferring knowledge between teams with a variety of different work backgrounds and experiences allows them to speak a common language. Combined with an extensive programme of digital upskilling at all of its depots, Hitachi is creating a digital workforce ready to deal with an even greater rate of technological change.

The benefits of digital are making a real difference in the rail sector, as can be seen every day. The ‘digital railway’ is a truly exciting opportunity and will deliver tangible benefits on reliability, frequency and capacity. As a sector, we need to collaborate, be bold and to put digital at the heart of a modern and sustainable railway.

This article was written by Philip Hewlett, business change and IT development programme manager at Hitachi Rail.

Read more: Signalling procurement enters the Digital Age



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