Digital Twins Series: Insights and Conclusions

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As our blog series comes to an end, we reflect on the opportunities and challenges digital twins have brought to rail so far, and the lessons we can learn to reap future benefits. 

In this blog series, we have looked at the concept of digital twins, and explored ways to classify different iterations of digital twin development. We have reported on both recent and planned digital twin implementations, developed for a diverse range of railway applications on behalf of numerous stakeholders. Operational performance, specific station design, station management and staff training have all benefitted from using twins to derive enhanced value from data assets. These cover a range of needs including achieving better access to data they already owned, or combining it in original or different ways, or as the impetus to collect new forms of data to facilitate the future development of new business insights and enable novel or enhanced organisational capabilities.

The power of digital twins lies in allowing data to be combined in a way that generates new operational insights, and thus enhanced decision-making. Rail is well placed to reap the benefits of digital twins, and there is clear appetite to do so, evidenced by the projects we’ve identified in this series. 

As an industry, this technology opens the opportunity to combine a wealth of data into both representation and decision support digital twins. As other industries begin to develop digital twins, rail, which already navigates a complex operational network and supply chain incorporating dynamic fixed, moving, physical and digital assets, can pave the way to demonstrate how complex systems can be combined, using data originating from multiple different sources and actors.

There are clear challenges in getting from digital data to digital twin, and from digital twin to digital twin ecosystem. Over the course of this series, the experiences shared by academics, industry members and data specialists has highlighted their impact on how effectively rail as a sector can deploy this technology. Collectively, we must approach these challenges with a solid plan to ensure accurate, reliable, useful and sustainable solutions are developed.

Key Insights

  • Being prepared to change: cultural and organisational shifts may be necessary for rail companies to fully embrace digital twins. Additional education and knowledge transfer may be important to communicate the needs and benefits of digital twins to strategic decision makers.
  • Applying the appropriate expertise: Toshiba and Greater Anglia achieved great success with a co-developed digital twin, with both parties adopting roles which played to their respective organisational strengths and knowledge. Toshiba’s experience in making digital twins of their factories enabled them to develop a model which successfully combined the data needed for Greater Anglia’s timetable twin. Greater Anglia’s in-house experts on timetable planning, helped ensure the model appropriately accounted for the many interdependencies between the different data. Together, they created an accurate representation of a complex system, which expert timetable planners piloted, and later used to augment the knowledge of staff to create new, robust timetables. We anticipate seeing further digital twin collaborations between rail and non-rail sector and/or technology partners, with each party contributing its own valuable expertise.
  • Incorporating the right data: to serve its purpose, a digital twin relies on the right data, updated at the right time and available for analysis in the right way. Therefore, in specifying and creating a twin it is crucial to consider functionality, architecture, the data required. It is also important to assess its associated integrity and availability, and understand where and how the data will be uploaded, stored and secured.  The Gemini principles set out by the National Digital Twin (NDT) program can help in thinking through considerations.
  • Providing appropriate education: digital twins are intended to enhance the capabilities of human workers, from making better and more timely decisions, through to education and learning. For this to be the case, staff need to understand how to work with this technology. Furthermore, creating, maintaining and operating digital twins will require workers with entirely new skillsets, such as cyber resilience, data science, data modelling, software development and more. Companies looking to implement digital twins will need to incorporate these prospective needs in their recruitment and training plans

Looking to the future, we expect to see more digital twin deployments in rail. Technological advances will increase the power of digital twins; smarter algorithms enabled by new developments in Artificial Intelligence, more powerful connectivity provided by 5G, and the proliferation of data generated by IoT-connected and edge-computing devices are just some examples. With these new opportunities, however, we can also anticipate new risks. As one example, by digitally connecting large parts of the railway we dramatically increase the ‘attack surface’ of rail operations from a cybersecurity standpoint. This is an issue we must prepare for and RSSB plans to examine the topic in detail later this year. 

Since the launch of this series at the end of 2019, we have seen growing interest in digital twins from across the sector to match our own. This is exemplified by the number of events and articles on the subject being organised and published. As awareness of and enthusiasm for digital twins grows, RSSB’s Horizon Scanning Team is eager to publish more experiences from rail stakeholders. These will be published as an extension to this collection looking at the challenges and benefits of implementing digital twin. If you have anything to share, get in touch!


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Claire Shooter
Tel: 020 3142 5695
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