BimScaler Blog – A digital twins technology is a 3D model based on data from sensors, simulations, and other sources, which enables the replication of the behaviour of the real thing.
This loop ensures synchronisation between the digital twin and the real-world asset, providing insights into their performance and any issues.
Digital twin technology is a valuable tool for improving efficiency, predicting failures and making better decisions in a number of areas, including healthcare, manufacturing and urban planning.
What is Digital Twins Technology?
Digital twins technology is a big step forward in data analytics and digital transformation.
Maggie Mashaly says in “Connecting the Twins: A Review on Digital Twin Technology & its Networking Requirements,” a digital twin is a digital replica of a physical system that continuously collects data from its real-world counterpart to simulate and analyse its behaviour in real time.
This constant flow of data means the digital twin can mirror the physical system’s state, predict future outcomes and make operations more efficient.
This means digital twins technology is a key tool for making data-driven decisions and keeping an eye on complex systems.
This digital twin technology can validate and simulate the physical twin’s present and future behaviours, which makes it a must-have for managing the lifecycle of products and services and for predictive maintenance across various industries.
Key Components of Digital Twins Technology
There are a few key parts to the architecture of digital twins. All of these parts work together to make sure that the physical and digital worlds can interact seamlessly.
In this section, we’ll take a closer look at these fundamental components.
Physical Entity
The idea behind digital twins is simple: you have the physical entity, which is the actual object or system being replicated.
According to Botín-Sanabria et al. in “Digital Twin Technology Challenges and Applications: A Comprehensive Review,” this entity is equipped with sensors and IoT devices that collect real-time data.
These sensors are a key part of the system, as they capture the status and performance of the physical system, providing the data needed for the digital twin.
For instance, in a manufacturing environment, sensors on machinery gather data on operational parameters like temperature, pressure, and vibration.
This data is then sent to the digital model, which lets you monitor and analyse in real time.
Digital Model
The digital model is a virtual version of the real thing, created using advanced 3D modelling and simulation software.
This model isn’t static; it’s constantly evolving based on the data it receives from the physical entity.
For Mashaly, the digital model is an exact replica that can simulate different scenarios and predict outcomes.
Take the construction industry, for example. Digital models of buildings can be used to test how they’ll perform structurally in different conditions. This helps engineers spot potential issues before they become problems.
Data Integration
Getting all the data into one place is an important part of making sure the digital model is always accurate and up to date.
The digital model is updated in real time with data from the physical entity, which means we can run precise simulations and analyses.
Botín-Sanabria et al. says it’s crucial to have seamless data integration to keep the physical and digital worlds in sync.
This integration lets you make real-time updates and adjustments to the digital twin, so it reflects any changes or anomalies you find in the physical entity.
Take healthcare, for instance. If you monitor a patient’s vital signs digitally, you can use that data to create a digital twin that shows how their health is changing in real time.
That way, you can intervene quickly when something’s wrong.
Connectivity
We can link the physical entity to the digital model because we have some pretty solid communication networks in place.
These networks make sure all the data is transferred all the time, so you can monitor things in real time and make updates as needed.
Mashalya’s review shows us why we need low-latency, high-reliability networks to support the data flow between physical and digital twins.
Connectivity is a big part of what makes a smart city work, for instance.
It lets city planners integrate all the different urban systems into one digital twin, which is a great tool for managing infrastructure and services.
Analytics
We should use advanced analytics, AI, and machine learning algorithms to process the data collected by the digital twin.
These technologies help us to gain valuable insights, make predictions and identify opportunities for improvement.
As Botín-Sanabria et al. said in their review, these analytical tools are key for turning raw data into something we can use.
For example, predictive maintenance algorithms can analyse data from industrial equipment to predict when something might fail and schedule maintenance in advance.
For an idea of the advantages, kindly read “From Factory Floors to Hospital Halls: Various Benefits of Digital Twins.”
Applications of Digital Twins Technology
Digital twins can be used in many different industries, and they offer some pretty big benefits in each case.
As Hossein Omrany points out in “Digital Twins in the Construction Industry: A Comprehensive Review of Current Implementations, Enabling Technologies, and Future Directions,” the digital twins help with virtual design and construction by creating high-fidelity models of physical assets.
These models let engineers and designers analyse and optimise in great detail, which helps them make informed decisions throughout the design and development process.
In healthcare, digital twins can create digital replicas of human bodies. This lets medical professionals monitor vital signs, predict health issues, and train themselves.
This is a big deal for proactive health management and remote surgeries.
Similarly, in smart cities, digital twins help us visualise and manage city resources, infrastructure and transportation systems more efficiently, which is great for urban planning and operations.
Digital twins are used a lot in manufacturing to keep an eye on production lines, predict when maintenance is needed, and make processes more efficient.
For example, General Electric uses digital twins to keep an eye on their aircraft engines in real time and predict when they might need maintenance.
What Software is Used for Digital Twins?
The software you choose will depend on what you need it for and what your industry requires.
In this section, we’ll take a look at some of the main software solutions on the market to help us utilise digital twins technology.
CAD and BIM Tools
One of the key things in developing digital twins is using Computer-Aided Design (CAD) and Building Information Modelling (BIM) tools.
Software like Autodesk Revit and BIM 360 are really important for creating detailed digital models of buildings and infrastructure.
These tools let architects and engineers design, visualise, and simulate structures in a virtual environment, making sure that the digital twin is an accurate reflection of the physical building.
As Botín-Sanabria et al. point out, CAD and BIM tools are essential for getting digital twins off the ground. They provide the precision and detail needed for complex structures.
IoT Platforms
For a digital twin to work properly, it needs to get real-time data from the physical version all the time. This is where IoT platforms come in.
Platforms like Microsoft Azure IoT and PTC ThingWorx provide the key connectivity and data integration capabilities needed to feed real-time data into digital twins.
These platforms make it easy to share information between the physical and digital worlds, so the digital twin always has the latest operational data.
Simulation Software
Tools like ANSYS and Simulink let engineers run complex simulations and analyses, so they can test out different scenarios and make data-driven decisions.
These tools are really useful in industries like manufacturing and aerospace, where getting the simulations just right can lead to big improvements in efficiency and safety.
Simulation software is great for checking that the digital twin models are working as they should, and that they can predict what will happen in the future, even when things change.
Data Analytics and AI
The real power of digital twins is that they can generate useful insights by using advanced data analytics and artificial intelligence.
Software like IBM Watson and SAP Leonardo use AI and machine learning to analyse all the data collected by digital twins.
These tools can predict what’s going to happen and make operations more efficient by spotting patterns and trends that you might not see if you were just looking at the data manually.
There have been lots of paper reviews on this, including ones by Mashalya and Botín-Sanabria et al.
They talk a lot about how AI and data analytics can help us make better decisions and work more efficiently.
Take a look at “Know Your Enemies: A Strategic Approach to Digital Twins Challenges,” to get an idea of the challenges we’re facing.
How to Make Digital Twins Technology Work for You?
In addition to the fundamental issues already discussed, we must also address some challenges that require our attention.
The technical bits and pieces of putting it into practice, the need for specific know-how, and the regular upkeep can be pretty tricky to get your head around.
That’s why we really think you’ll love using BIM Scaler as your BIM management support system.
BIM Scaler is an Australian company on a mission to make your project life easier. We provide customised BIM and digital twin solutions for businesses in the AEC industry.
We’re here to help with anything and everything, from CAD and BIM management to putting together a full implementation strategy.
We’d love for you to take a look at what we did with K2LD Architects.
We set up a great CAD and BIM management system for K2LD Architects to improve workflows, improve collaboration, and accelerate project completion.
We’d absolutely love to tell you more about how BIM Scaler can help you with your construction projects.
So, we would be grateful if you could take the time to visit our CAD & BIM Management Support page to learn more.
Alternatively, you can contact us today to arrange a lunch meeting. We would be delighted to demonstrate our services to you.
In Closing
The success of digital twins technology relies on a mix of sophisticated software tools that cover various aspects of design, connectivity, simulation, and data analysis.
As digital twins technology keeps on developing, we’ll see it being used in lots more ways, which will lead to more new ideas and improvements in lots of different sectors.
