BimScaler Blog – Digital twins are basically virtual copies of physical assets, processes, or systems. Isn’t that interesting? But how do digital twins work?
We all know that digital twins (DTs) are digital replicas of physical entities – ranging from products and processes to entire systems – used to simulate, predict and optimise real-world performance.
These virtual models are linked to their physical counterparts through real-time data, so they can give each other feedback all the time.
But how do they actually work, and what’s their impact on the AEC industry?
The Technology Behind Digital Twins
Digital twins are really cool virtual replicas of physical assets, processes, or systems that can simulate, predict, and optimise real-world performance.
They use a bunch of different tech, like the Internet of Things (IoT), artificial intelligence (AI), machine learning, and cloud computing.
Remember, the idea is to create digital versions of real-world things that look and act just like the originals.
At the heart of digital twins is the Internet of Things (IoT), which involves placing sensors and devices to gather real-time data from physical assets.
This data collection is foundational, enabling us to monitor and interact with our physical and digital counterparts continuously.
As explained in the white paper “Digital Twins for the Built Environment” by Alexandra Bolton and colleagues, the technology stack for digital twins also includes artificial intelligence (AI) and machine learning (ML), which process and analyse the data to generate useful insights.
On top of that, cloud computing is a big part of the digital twin ecosystem. It gives us the computing power and storage space we need to handle all that data.
This part of the tech lets you create scalable and flexible solutions that can handle growing data sets as projects progress.
According to Dr Ken Dooley in ‘Building Digital Twins’, it’s a big deal to integrate data from different sources, like Building Information Models (BIM), asset management systems and IoT devices, to create a comprehensive and dynamic digital representation of physical assets.
One of the great things about digital twins is that they can run simulations and predictive models.
This means that stakeholders can see what might go wrong, make their operations more efficient, and make better decisions.
The combination of real-time data and predictive analytics creates a feedback loop that helps both the physical asset and its digital twin to improve all the time, leading to better performance and efficiency.
To gain a 360° perspective, kindly read “What is Digital Twin? Not Your Average Virtual Copy – Here’s Why It Matters.”
How Do Digital Twins Work?
Data Collection and Integration
The first step in creating a digital twin is to collect and integrate the data. Please note that DTs rely on real-time data gathered from physical assets through various sensors and IoT devices.
These sensors collect all kinds of data, including temperature, pressure, humidity, vibration, and other relevant parameters.
For instance, in the built environment, sensors in buildings can monitor things like energy consumption, occupancy levels and environmental conditions.
This first round of data collection is the basis for building the digital twin.
The white paper “Digital Twins for the Built Environment” by the Institution of Engineering and Technology (IET) states that integrating this data into a centralised platform is vital.
The process is all about making sure the data from different sources is in sync and easily accessible.
In their report, Alexandra Bolton and her colleagues also point out how essential it is to have data standards and interoperability to make sure everything integrates smoothly and that the data is reliable.
Real-Time Monitoring and Analysis
Once the data is integrated, the digital twin keeps an eye on the physical asset in real-time.
This means using some pretty advanced analytics and machine learning algorithms to process the data that comes in and spot patterns, anomalies and trends.
The digital twin can give you feedback in real time, so you can make decisions before it’s too late.
In their paper, “Building Digital Twins” Dr. Ken Dooley and his colleagues talk about how digital twins help businesses work more efficiently by analysing data in real time.
For instance, in a manufacturing environment, a digital twin can keep an eye on equipment performance, predict potential issues, and suggest maintenance activities before things get out of hand.
Simulation and Modelling
One of the best things about digital twins is that they can run simulations and create predictive models.
By creating a digital version of the physical asset, engineers and operators can test different scenarios and predict outcomes without putting the actual asset at risk.
Cristina Savian’s research in “Digital Twins for the Built Environment” shows how simulations can help us make better design and operational decisions.
For instance, during the design phase of a construction project, digital twins can show how different HVAC systems affect energy efficiency and occupant comfort.
Predictive Analytics and Feedback Loops
Predictive analytics use historical and real-time data to work out what’s going to happen in the future and spot potential problems before they actually happen.
This is made even better by using feedback loops, where the insights gained from the digital twin are used to make the models better and improve both the digital and physical assets all the time.
The “Digital Twins for the Built Environment” report shows how feedback loops help us make continuous improvements.
So, if a digital twin spots a problem with a building’s HVAC system, that info can be used to tweak the maintenance schedule and take corrective action.
If you want to see a good example of BIM in action, please refer to “Building Information Modelling (BIM) in Urban Planning: Application, Benefits, and Challenges“
How Digital Twins Connect Design and Build Workflows
In the Architecture, Engineering, and Construction (AEC) industry, digital twins help to bridge the gap between the design and build phases.
This bridge makes sure all the information flows smoothly and that the construction process sticks to the original design.
During the design phase, digital twins let architects and engineers create detailed and accurate models that include all the right stuff, like materials, structural loads, and environmental impacts.
As more data comes in, the models keep on evolving, so the design is always based on the latest information.
During construction, digital twins are a great way to keep everything on track.
By comparing the physical construction with the digital model, any discrepancies can be spotted and fixed quickly, so the building is built as it should be.
Digital twins also help project managers keep on top of what’s going on by showing them what’s happening on site in real time.
Project managers can keep an eye on how different parts of the project are going, make sure they’re using the right resources, and make sure they stick to the timeline.
Once construction is finished, digital twins keep on being useful by checking how the building is performing.
Sensors built into the building send data back to the digital twin, so it can assess things like energy use, indoor air quality and how the building is used at any given time.
This ongoing monitoring helps make sure the building is running as well as it can be and guides maintenance activities.
For instance, a digital twin can let facility managers know about potential issues like equipment malfunctions or inefficient energy use, so they can fix them quickly and cut down on costs.
Another useful source of information is Ashwin Agrawal’s paper, “Digital Twin: From Concept to Practice.”
How do You Implement Digital Twins?
The first thing to do is to make sure you know what you’re trying to achieve. What do you want to achieve with the digital twin?
Objectives can be all over the place, from making sure maintenance schedules are as efficient as they can be to improving operational efficiency or enhancing the user experience.
Setting clear goals helps guide the implementation process and ensures that the digital twin delivers value.
Next, get some sensors and IoT devices to collect data from the physical asset in real time.
The type of sensors you use and the data you collect will depend on what you want to achieve.
If you’re looking to monitor energy usage in a building, you’ll need sensors that track electricity consumption, HVAC performance, and lighting levels.
Once you’ve got the data, you need to get it into a central digital twin platform.
This means setting up data pipelines that make sure the data flows smoothly from the physical asset to the digital twin.
Integration also means making sure all the data from different sources is in the same place so you can see the whole picture.
The next step is to develop detailed virtual models of the physical asset.
This means using the data we’ve collected to create accurate and dynamic models that reflect real-world conditions.
Then we use simulation tools to test different scenarios and predict what’ll happen.
For instance, in the case of a smart building, simulations can show how different HVAC settings affect energy efficiency and occupant comfort.
Then, make sure you put in place systems for real-time monitoring and analysis.
This means setting up dashboards and analytics tools that show you what’s going on with the asset all the time.
Monitoring in real time helps you spot any issues quickly and makes sure the digital twin stays an accurate reflection of the physical asset.
Keep the digital twin and the physical asset in sync by setting up feedback mechanisms to continuously improve both.
Use the insights you get from the digital twin to make updates to the models, update the data sources, and optimise operations.
BIM Scaler is a great example of a platform that can help you implement digital twins.
At BIM Scaler, we provide customised IT helpdesk management solutions to make it easy to integrate digital twins into existing workflows.
Our CAD and BIM management services make sure that data from different sources is all in one place, so you can make the best decisions and get the most out of it.
Yes, we at BIM Scaler can help you get the most out of digital twins.
Our platform makes it easier for organisations to implement and manage digital twins by supporting real-time data collection, integration and analysis.
If you want to know more, kindly visit BIM Scaler and find out how they can help you make the most of digital twins to get the best out of your assets and improve performance.
In Closing
By making smart decisions based on these insights, companies can make their operations better.
If you want to get the most out of digital twins, you need to take a strategic approach. This means collecting data, integrating it, and making sure it keeps improving.
BIM Scaler is a great way for organisations to make the most of digital twins, helping to drive innovation and growth in the AEC industry and beyond.
With their transformative potential, it’s worth exploring how do digital twins work.
