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Understanding Digital Twins
For many organizations, one of the biggest barriers to digital twin adoption is an all-too-common assumption that the technology isn’t right for their operation. Often, this reluctance stems from the belief that they have neither the necessary tools and processes in place nor the ability to invest in them.
However, it’s far more accurate to view the implementation of digital twins as a journey, where the technology matures in tandem with the organization, its operations, and the assets the tool will capture.
Part of the challenge hangs on the mysticism that surrounds digital twins as an advanced and arcane technology. The simplest definition of a digital twin is a virtual representation of a physical object which captures asset, system, and process data. A twin can be as basic or static as a one-dimensional CAD file comprising dimensional or geometric information. From there, the goal should be to develop a highly dynamic, 3-D, automated twin that mimics the behavior of the asset in real-time, allowing users to spot trends and predict the future.
The Five Stages of Digital Twin Evolution
The goal is to identify where the organization sits between these two plot points. Usefully, independent research and advisory firm Verdantix has split the journey into five key stages of evolution:
- Descriptive twin
- Informative twin
- Predictive twin
- Comprehensive twin
- Autonomous twin
For some organizations, the first step might be to create an asset and space inventory of their building(s) before uploading that data to a CAD file or similar visualization technology. This represents the descriptive stage and forms the live, editable foundation for every bit of data that is overlayed afterward.
Once the twin has these initial data sets, the next step is to transform the digital twin into a 2-D replica with more detailed information. After equipping assets with IoT sensors, users can add operational and sensory data, such as temperature and vibration information. At this stage, the organization can begin to understand how the different assets captured in the digital twin operate together and build a real-time picture of the physical building.
With this real-time information, users start building a 3-D twin, incorporating data from sensors, enterprise systems and other external sources, to develop a more holistic understanding of the asset. At this point, the digital twin contains historical data that can be used to identify trends, run simulations and scenario plan.
The ultimate goal, and final stage, for any digital twin is continuous operational data. In theory, the twin will have the power to act autonomously based on the insights from its dynamic data.
This capability ensures more responsive building management and accurate decision-making based on better data.
The Potential of Digital Twins
As digital twins incorporate smarter technology and more dynamic data, their potential increases. Combining real-time data with automation and AI will help create autonomous buildings, where a bi-directional link between the physical building and its dynamic digital copy allows the technology to automate actions regarding asset, space, and environmental management.
The digital twin, when integrated with IWMS software, could generate a work order that dispatches an engineer. From a space management perspective, it could just as easily open a reservable meeting room or desk space to the broader office population if capacity is nearly reached.
Similarly, the technology could automatically adjust environmental controls for temperature, lighting, and indoor air quality, or even open windows if sensors can capture outdoor conditions.
The Accessibility of Digital Twin Technology
For building managers that are still skeptical about implementing digital twin technology, it’s important to note that organizations can start small. Organizations can initiate pilot projects that serve as proof of concepts. One option is to develop a digital twin for single assets or specific areas of a building. This tactic allows users to experiment with integrating data and vizualisation techniques.
Where an organization is on the maturity journey depends on a whole host of factors, including the industry they operate in, their business objectives, the capability of their in-house teams and technology partners, and lots more. But this shouldn’t serve as a barrier to taking advantage of digital twins, which have the potential to transform an organization’s building and property strategy.
For more information about how QFM, Service Works Global’s facilities and asset management software can help improve proactive maintenance at your organisation, contact us for a chat or a demonstration.
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