Interscale Content Hub – A digital twin is basically a virtual copy of a physical asset, like a building, bridge, or even an entire city. We were all aware of this from the start. But, how to create digital twins?
These digital twins aren’t just static models. They’re dynamic, living representations that receive real-time data from their physical counterparts, which allows for better understanding, analysis, and management.
That’s why it’s so important to get every detail right when creating digital twins, as they’re constantly moving.
Benefits of Digital Twins
Digital twins are great for boosting efficiency, keeping on top of maintenance, and improving product design.
A Gartner survey reported in “Gartner Survey Reveals Digital Twins Are Entering Mainstream Use” found that 75% of organizations involved in IoT projects either used or planned to use digital twins within a year.
Plus, a market research report by MarketsandMarkets™ says the global digital twin market was worth USD 3.1 billion in 2020 and is set to reach USD 48.2 billion by 2026, growing at a CAGR of 58% during the forecast period.
Those numbers show just how big the impact of digital twins is. These digital twins let you monitor, simulate, and optimize in real time, which means less downtime and cost savings.
For another example, in the Siemens presentation article “Real-time guidance for workers using smartwatches, AI, and the digital twin,” Dr. Hugo Zupan explains how to use AI and digital twin technology to provide real-time guidance to workers through smartwatches.
For fundamental reference, please refer to “What is Digital Twin? How Digital Twins Transform for Smarter Projects?“
What is Needed for a Digital Twin?
To create a digital twin, you need a few key things. First, you need the physical asset, which is the real-world object or system you’re going to replicate.
Secondly, you need to create a detailed digital replica of the physical asset, which we call the virtual model.
Finally, it’s important to have a continuous data flow so that the physical asset and the virtual model are always in sync.
In Granlund’s report, “Building Digital Twins,” Dr. Ken Dooley and José Carlos Camposano point out the importance of a master geometry model, especially for complex digital twins that serve as the foundation for simpler ones.
Integrating building management systems, IoT devices, and other dynamic data sources is key to enhancing the static BIM models used during the design and construction phases.
The success of digital twins also depends on scalable solutions that can manage and update static and dynamic information efficiently throughout the asset’s life cycle.
Key Components of a Digital Twin
Sensors and IoT devices, which collect real-time data from the physical asset, are what make up a digital twin.
A data integration platform is needed to bring all the different data sources together and process it. Simulation software is used to create and update the virtual model based on the data that comes in.
Analytics tools are key for analyzing data to get insights and predict what’ll happen to the asset in the future.
Finally, a user interface lets users interact with the digital twin and see data and simulations.
Dr. Ken Dooley and José Carlos Camposano have identified four different types of digital twins based on how complex they are:
- As-built digital twins
- Building Services digital twins
- Interactive Floorplan digital twins
- Business Intelligence Dashboard digital twins.
The as-built digital twin includes detailed 3D models that are filled out with data from building management systems and IoT devices.
On the other hand, simpler twins, like the Interactive Floorplan digital twin, use up-to-date 2D plan drawings with static and dynamic data.
Granlund’s case studies, like the ones involving the Easton shopping center and Kuopio University Hospital, show how digital twins can be used in real-world situations to make things easier and more efficient.
The case studies showed how digital twins could help make things more efficient, help with maintenance, and support different business cases, from virtual tours to energy optimization and fault detection.
Step-by-Step Guide to Creating Digital Twins
First of all, it’s not as simple as just turning your palm. Building a digital twin is complex, but there are ways you can break it down into steps you can take one at a time.
This guide draws on insights from Dr. Ken Dooley’s report, “Building Digital Twins,” and the comprehensive research by Granlund in their industry report.
Step 1: Data Collection
The first step in creating a digital twin is collecting data. According to Granlund’s report, this means gathering lots of data from different sources about the physical asset.
The data types include things like geometric data from BIM models, sensor data from IoT devices, and historical performance data.
It’s important that the data collected is accurate and comprehensive so that the digital twin accurately reflects the physical asset.
Step 2: Data Transmission
Once the data is collected, it needs to be sent over to the digital twin platform as efficiently as possible. Dr. Ken Dooley says keeping the data in sync with the physical asset is key.
This can be done by using solid data communication protocols and secure networks to make sure that data doesn’t get lost and that everything is reliable.
Step 3: Data Processing and Analysis
Turning raw data into actionable insights is all about data processing and analysis.
Dr. Ken Dooley’s report shows how we’re using advanced analytics tools and AI algorithms to process the data.
This next step is about filtering, validating, and analyzing data to identify patterns, anomalies, and insights that can help optimize the performance of the physical asset.
Step 4: Building the Virtual Model
The virtual model is created using the data that’s been collected and processed to represent the physical asset digitally.
This model includes detailed 3D representations and integrates real-time data to show how the asset behaves.
Dr. Ken Dooley says the virtual model has to be dynamic and able to update in real time to reflect changes in the physical asset accurately.
Step 5: Implementing Feedback Loops
The final step is to implement feedback loops, which ensures continuous improvement and optimization.
Granlund’s research shows that it’s really important to set up a way for the digital twin to send feedback to the physical asset.
This could mean tweaking the operational parameters based on what the digital twin is telling us, which should lead to better performance and efficiency.
For another technical reference, please refer to “Your Guide to Understanding How Digital Twins Work for Smarter Projects.”
Best Practices and Considerations
When you adopt the best practices and consider the key factors, you’re more likely to have a successful implementation of digital twins. Dr. Ken Dooley’s research offers some great insights into these aspects.
First, it’s best to start with a simple version of the digital twin and then gradually make it more complex.
Granlund’s report suggests an iterative approach, where digital twins are developed in stages, allowing for adjustments based on real-world feedback and evolving requirements.
Secondly, data security and privacy are really non-negotiable. Digital twins rely on a lot of data, so it’s important to make sure that this data is kept safe from breaches.
It’s also vital to have strong cybersecurity measures in place and to comply with data protection regulations.
According to Jernej Protner, Marko Simic, and Niko Herakovic, in their study on data-driven digital twins, “A Five-Step Approach to Planning Data-Driven Digital Twins for Discrete Manufacturing Systems,” managing large amounts of heterogeneous data and ensuring secure data exchange between physical and digital entities is a significant challenge.
Therefore, establishing a secure framework from the outset is vital to safeguard sensitive information.
Thirdly, keeping everyone on the same page and working together is key. For digital twins to be successful, it’s important to make sure that data from different sources and departments can be easily integrated.
Granlund says that building owners, facility managers, and technology providers need to work together to create a unified digital twin ecosystem.
Finally, continuous innovation and adaptation are key. The digital twin field is changing fast, so it’s important to keep up with the latest tech and methods.
Dr. Ken Dooley’s report shows how important it is to keep on researching and developing digital twins to make them better and deal with new problems.
We also suggest you read Jeff LeBlanc’s presentation “Creating Device-Accurate Digital Twins Using ICS’ Rapid Development Technique,” if you’re looking for more technical info.
How to Create Digital Twins with Good Supporting System
Building Information Modeling (BIM) is a great tool for managing your construction projects, but it can be complex and time-consuming.
What if there was a way to make your BIM workflow easier, integrate your data more smoothly, and even use it to create digital twins for better decision-making?
Our team has created comprehensive solutions exactly tailored to support BIM and the creation of digital twins.
Our BIM management services are all about customization. They’re tailored to meet your specific needs.
One common belief is that it’s nearly impossible to integrate diverse data sources and platforms into a single digital twin model without extensive technical expertise.
At Interscale, we use our deep expertise in data integration to make sure that digital twins are created and maintained seamlessly.
This expertise lets you make your project management better, get better data, and make your operations more efficient—without the usual headaches.
If you want to know more about our BIM management services, kindly check our Interscale BIM Management Support page.
Additionally, we understand the value of personalized guidance. So, if you have any questions or need a 1-on-1 discussion, we’re here for you 24/7.
Conclusion
Digital twins are dynamic, virtual replicas of physical assets, designed to enhance efficiency and decision-making across industries.
It means we can be sure digital twins will keep on helping us in new ways.
That’s why it’s a good idea to keep up on how to create digital twins to make sure you’re getting the most out of digital twins.
