Demystifying the digital twin

September 28, 2018

digital-twin-image-1-thumbnailI’m a rock climber.  After my wife and kids, climbing is my passion.  Of course, there are inherent risks to climbing (as to anything in life), so I try to manage and mitigate those risks as best I can. And managing risk is all about information.  

Before a big climb I try to capture as much information about my chosen route as possible. I do this by researching guidebooks and maps, quizzing friends who have climbed the route, studying weather forecasts, and referencing on-line sources like Mountain Project and Google Maps. I’m trying to capture a detailed mapping of the route’s physical features, the ever-evolving condition of the rock, and an accurate prediction of the expected weather. I endeavour to create a model of the climb – a sort of digital twin – that helps me learn about what I might encounter when I climb the route, and how best to prepare.  

This concept of a digital twin also has significant importance to us at SNC-Lavalin as it can create great value, particularly if it is leveraged throughout the design-build-operate lifecycle of infrastructure and other assets.  

Put simply, a digital twin is a digital model of a physical thing. The digital twin can have several roles – it can represent the design of a physical thing before it is built, the progress of its construction, or its condition and health when it is in operation. Other terms like BIM, BLM and AIM represent similar concepts (with some important distinctions), but they are all are essentially driving at the same thing. 

The digital twin has long existed, in different forms, as a part of the design and build process. A digital design, even if it is a 2D model, is a rudimentary form of a digital twin. Of course, most of our design work is now moving to 3D, and BIM has continued to expand the standard for these models to include additional dimensions that cover things like time (4D BIM) and cost (5D BIM).  

These more advanced digital twins provide significant value by allowing us to visualize what is being built and share this knowledge with stakeholders.  They can answer the questions:  What will it really look like? and Will the owner like it?  These models also allow us to identify potential conflicts, optimize efficiency, and track progress.  For example, they can answer:  Is there room in that wall for both the electric conduit and the water pipes? Can I have the electricians and the plumbers working at the same time? and Are we on target with our schedule and budget?digital-twin-image-2-thumbnail

The value of the digital twin also extends into the operations phase. However, too often in our industry, the digital twin is not maintained during construction and into operations.  And there can be major discrepancies between the initial design and what is eventually built and put into operation.  Like the evolution of a rock climb, features and conditions can change over time.  

However, SNC-Lavalin is uniquely positioned to reverse this industry trend because we can manage and control the end-to-end value chain.  That means we can ensure that the digital twin is maintained throughout the design-build-operate lifecycle.  We can also incorporate information about how to operate the physical asset, and we can capture data from sensors to get a view of how the asset is performing.  These capabilities can unlock significant value in the operations phase, which often represents 80% or more of the total cost of ownership.  

The digital twin can be used to train site operators, similar to rehearsing the moves of a difficult rock climb on an artificial rock wall.  This is particularly valuable for remote facilities like off-shore oil rigs, or high-risk environments like nuclear power plants.  Immersive training can do the same job as on-site training, but in a safer and more cost-effective way. 

The digital twin can also be used in the operations phase to monitor and optimize asset performance, and to predict and prevent asset failure.  For assets as diverse as commuter rail lines and power generation plants, this means increasing output (e.g. more passengers traveling or power produced) and decreasing outages (e.g. less delays or costly shutdowns).  

Like being able to prepare for a pending snow storm on a mountain, it’s important to be able to predict and prepare for pending issues with infrastructure and other assets to reduce risk and improve outcomes.  And you can’t do that if you don’t have an up to date digital twin.  

Please feel free to contact me ( if you would like to discuss how a digital twin could help on your projects.  

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