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Since digital twins technology covers an asset’s whole lifecycle, rail infrastructure and rolling stock have a lot of potential, particularly in terms of preventive maintenance.
In reality, the prediction and identification of track and vehicle components that offer a risk of failure can both benefit greatly from the use of digital twins in asset modelling. This makes sure that the lessons discovered as a result of these digital solutions are applied to new goods and systems and help to improve designs in line with operational needs.
Furthermore, digital twins can help foresee changes that will occur during the project execution when planning and building a new railway or piece of rolling equipment, as well as during procedures of upgrade or renewal.
The UK Rail Digital Twin Market accounted for $XX Billion in 2023 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
Cardiff University’s computational urban sustainability platform was used by Atkins and Cardiff University to create a digital twin of the station at Network Rail’s request (CUSP). The digital twin can recreate the station’s current energy use and has found efficiency solutions that might increase the station’s energy performance by a fifth using historical and existing data as well as computer modelling.
The collaboration between Atkins and Cardiff University and Network Rail strengthens the digital twin solutions being offered globally in the rail industry. Improved lighting controls that dim portions of the station when empty have been identified as energy-saving options for Reading station, along with turning off equipment like escalators when not in use or when train services aren’t running (such as overnight).
