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How Digital Twins Optimise Efficiency

As sensor technology proliferates, we are beginning to see more and more ways to enhance asset value and optimise efficiency. One of the most interesting began life at NASA, as a way for scientists on the ground to monitor their expensive assets in the air, or in space: the concept of the “digital twin” has been around for a while, and earlier versions of it – BIM, CAD, and so on – have been used effectively to model and monitor asset use in many different scenarios.

Businesses have used geometric modelling and simulation software for some time to monitor assets within a building. But in order to fully optimise asset use, it is necessary to consider the building as a whole and apply the newest digital twin technology, not merely updated computer-aided design models. IoT technology means that information about physical assets can be captured and monitored on a digital copy of the building, a blueprint that lets building owner-operators or facilities managers monitor and interact with the asset in real time.

More and more businesses are aware of the importance of asset monitoring. It adds value through reduced downtime, scheduled repairs, and increased overall efficiency. But the use of the digital twin extends far beyond this, into the realm of as-a-service business models: in order to comply with the ever-changing legislation, regulation, and taxation around carbon emissions, all new buildings will have to be ‘net-zero compliant’. As a result, sensor technology will have to be used much more purposefully to optimise energy efficiency and stay in line with the government’s target of reaching net-zero by 2050 in England, 2045 in Scotland.

IET and Atkins have produced a report that attempts to distil a clear definition of a digital twin, and the stages of complexity and connectivity that differentiate it from previous geometric modelling techniques: early stages of complexity involve simple asset management using a point cloud model attached to a BIM; more advanced stages involve real-time data capture and machine learning.[1] Unlike traditional geomodelling technology, the digital twin can ‘talk’ to its physical equivalent, so that assets can be remotely and even autonomously maintained, correcting errors and making adjustments without the need for human intervention. Again, the efficiency gains are clear.

As we look ahead to the future of climate action, digital twins could in theory be connected, as a recent article in the Financial Times points out, to form a kind of virtual city, allowing for data sharing, and a concerted effort on behalf of city authorities and residents to minimise emissions through informed decision making.[2] The Centre for Digital Built Britain (CDBB) echo this point in their research, and in their establishment a few years ago of a National Digital Twin Programme. But while the future of connected smart cities remains distant, the incremental benefits to the early adoption of digital twins – especially in achieving carbon reduction targets – are becoming more and more apparent.


[1] https://www.ft.com/content/15851b06-1b6f-11ea-81f0-0c253907d3e0

[2] https://www.building.co.uk/digital-transformation/as-important-as-the-internet-are-digital-twins-the-next-big-thing-for-construction/5102682.article

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