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Centre for Digital Built Britain

 

The Digital Twin Hub is a collaborative learning community, facilitated via an online portal, that will support collaboration related to the development, management and integration of digital twins for the built environment, including economic and social infrastructure. Here we launch the first in the series of monthly blog posts that will provide information on the latest thinking around digital twins, giving up to date information on trends and drivers in the sector.  

For the first DT Hub blog, Samuel Chorlton, Chair of the DT Hub, presents his thoughts on the opportunities for digital twins for infrastructure.  

Infrastructure Digital Twins? 

The term Digital Twin within the Infrastructure Domain has been gaining increasing prominence/relevance/recognition in the last couple of years as a result of a number of important publications: Data for the Public Good, Gemini Principles, Industrial Strategy, etc. With the buzz ever increasing, infrastructure asset owners are increasingly looking to this with aspirations of improving longer term commercial sustainability and resilience. Before we can understand whether this is a reality that can be achieved we must first understand the drivers that have led us to this point. 

The term digital twin is most commonly associated with the Engineering Sector with multiple success examples within core sectors such as Formula 1 and Aviation. Formula 1 companies now claim to have made such accurate digital representations of physical vehicles that the first instance a component may be introduced to a car is at a competitive racing event. It is therefore relatively easy to understand how organisations may look to translate these methods to other sectors where significant costs saving could be made through a reduction in failed enterprises. There is, however, one significant distinction that should be understood. Mechanical systems such as automotive vehicles have defined system boundaries that enable models to accurately represent all of the components. When you try and translate this to systems with non-definitive boundaries such as cities you quickly get caught up in the semantics of defining where a city starts and ends; not just spatially but in terms of the infrastructure that combines to create it. 

Discussion must therefore turn to how do we define a digital twin within the infrastructure domain, and, can they in turn be delivered. The short answer is that we shouldn’t get hung up by the definition because  that doesn’t prevent us from delivering value. This may sound like an oxymoron in its own right but instead we must explore digital twins as a mechanism through which to deliver a restricted number of organisational benefits over a predefined timeframe. The argument therefore over whether a digital representation is in fact a true Digital Twin becomes irrelevant and allows us to focus on whether this representation allows us to deliver these defined benefits. A sufficient working definition for a digital twin, can then be viewed as: a digital representation of the physical that is grounded in reality and can in turn influence positive change of the physical 

This resonates with the working definition provided within the Gemini Principles published by the Centre for Digital Built Britain which surmises them as: “What distinguishes a digital twin from any other digital model is its connection to the physical twin. Based on data from the physical asset or system, a digital twin unlocks value principally by supporting improved decision making, which creates the opportunity for positive feedback into the physical twin.” It is important to focus therefore on the component of unlocking value. The axioms of this value emanate from delivering positive change.  

The Digital Twin Hub Steering Group over the coming months will look to publish the first set of agreed business values as part of its Digital Twin Roadmap. These will allow organisations looking to adopt or continue the development of Digital Twins to understand where the core value stems from in their models and what subsequent gains may look to be achieved.  

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