Digital twins hold a virtual mirror up to a physical process, asset or service, helping businesses monitor, control and understand the ‘real’ version, and possibly simulate potential changes before they happen.
For years now, discrete sensors and devices have been helping teams track, monitor, and harvest data from almost any process or asset. When you have a 2D or 3D representation of the process (or product) and large quantities of live or historical data about every part of a process (or product), you can create its digital twin.
What is it?
A digital twin is a 2D or 3D digital representation of a physical asset, service, or process. It’s like a living blueprint of something — a trackable plan that doesn’t just reflect how that thing is designed, but how it’s really operating and what it really looks like today. Data streams into the 2D or 3D digital model and the model responds to what is happening in the real world on the same device.
They’re a major breakthrough for people that manage complex physical processes and produce highly technical products. With complete digital visibility of how their assets and processes are running, they can control machinery in real time, or easily spot things like impending or actual failures, sources of inefficiency, maintenance issues, and even seize opportunities for process streamlining.
Digital twins are extremely valuable modelling tools. Much like a development and test environment for software, digital twins can be used to digitally simulate potential changes to your processes. That could be anything from applying a new piece of machinery in an industrial process, to modelling the impacts of an environmental disaster on a supply chain process.
What’s in for you?
One of the biggest advantages of digital twins is improved process and asset performance visibility. They can map out even the most complex processes and operations in a way that can be easily understood by team members of any experience level.
You gain the ability to control machinery and use the 2D or 3D visualization to confirm that the desired behavior is occurring in the real world. Verification through data telemetry from the device is the feedback mechanism to ensure that what is commanded has actually happened. Visualization in turn eliminates an enormous amount of time understanding a dynamic system versus looking and tables and graphs of data.
The other major way that digital twins deliver value is by enabling digital simulation and modelling of future changes. Digital twins can simulate the impacts of things like proposed process improvements — helping teams build extremely compelling business cases for their projects.
That’s also extremely valuable for things like risk management and business continuity planning. By modelling the potential negative impacts of a shift in conditions, teams can build more robust plans for the future, and mitigate risks before they threaten their operations.
What are the trade offs?
To maintain an up-to-date digital reflection of a complex process or product, you need a continuous stream of rich data from that process or product. That in itself requires the deployment and maintenance of hundreds, or even thousands of discrete sensors.
2D and 3D digital twins deliver the greatest value when they’re created for highly complicated, multi-faceted processes or products. Invariably, these are also the things that demand the most data and most sensors to track effectively.
As a result, building and maintaining these digital twins can be a costly and complicated endeavour. You’ll want to be certain that the benefits they can deliver outweigh these costs.