Interscale Content Hub – Digital twins technology is the canvas stakeholders use to create a virtual replica of a physical object, process, or system.
This digital twin (DT) technology is becoming really useful in manufacturing, healthcare, automotive, and smart cities. It helps companies work more efficiently, save money, and innovate more.
All the cool new tech like IoT, AI, and machine learning are making digital twins more and more useful.
So, let’s look at some of the key technologies in digital twins.
How do Digital Twins Work?
Digital twins work by creating a digital copy of a physical thing, whether it’s a system, process, or object.
This digital copy is updated all the time with data from sensors and other IoT devices, so it can show you exactly what’s going on with the physical entity and how it’s performing.
In the final report for the Australian Meat Processor Corporation (AMPC), “Industry 4.0 – Evaluation of Digital Twins – Stage 1,” David Francis explains how digital twins are basically software entities that copy the way a physical system works using data from different sources.
These sources can include historical data, sensor data, and other relevant inputs that give you a good overview of the system’s current state and behavior.
For instance, in a meat processing plant, a digital twin can be used to simulate the production process, spot inefficiencies, and make operations more efficient without disrupting the actual workflow.
Let’s switch to Louise Anderson from Commonwealth Bank. Louise Anderson in “How data-led innovation is transforming business and the customer experience,” says one of the best things about DTs is how DTs can simulate business processes to predict outcomes and provide prescriptive recommendations.
For complex, interconnected processes where traditional process mapping falls short, this DTs capability is really useful.
Digital twins can help businesses test different scenarios, like changes in customer demand or supply chain disruptions. This lets them see what works best and choose the best approach.
Forecast’s paper, “Introducing The Digital Twin,” shows how digital twins can be used for “what-if” scenarios.
The paper recounts the Apollo 13 mission, for example, and how engineers used a digital twin to replicate the damaged spacecraft and devise a feasible re-entry strategy.
This historical example shows how digital twins can be really useful for solving problems and making decisions in the moment, even when things aren’t clear.
Key Technologies Involved
There are a few main technologies that make digital twins possible, from the Internet of Things (IoT) to artificial intelligence (AI), machine learning (ML), big data analytics, and cloud computing.
Internet of Things (IoT)
IoT devices are essential for digital twins because they provide the real-time data needed for accurate simulations.
Sensors built into physical assets collect data on different things like temperature, pressure, and movement. This data is then sent to the digital twin to keep it up to date.
As Louise Anderson says, data is what makes digital twins work. It gives them the power to provide useful insights and make operations more efficient.
Artificial Intelligence (AI) and Machine Learning (ML)
AI and ML algorithms look at all the data collected by IoT devices to spot patterns, predict what’ll happen, and make things run better.
David Francis’s report looks at how these technologies let digital twins do more than just analyze data.
The digital twins can also make recommendations and predict when something might need maintenance.
Big Data Analytics
Keeping up with the huge amounts of data produced by IoT devices is essential for digital twins to work properly.
Big data analytics makes it easy to process all this data, so you can analyze it in real time and make decisions on the spot.
Forecast’s detailed data integration shows how big data is key to creating accurate and reliable digital twins.
For a quick overview of the benefits of DTs, you can read “Slashing Costs: The Benefits of Digital Twins (and How to Get Started).”
Cloud Computing
Cloud platforms are great for storing and managing the data used by digital twins.
They make it easy to scale up and down, so digital twins can run smoothly even when there’s a lot of data or complex simulations.
The AMPC final report also mentions how cloud-based platforms like Prevu3D help us create and manage digital twins in real-time.
What Software is Used for Digital Twins?
As a disclaimer, in the meat processing industry, as David Francis discussed in his report for the AMPC, software like Prevu3D and NVIDIA Omniverse is really the key to the whole thing.
These platforms let you create high-fidelity digital twins that you can use for training, planning, and operational optimization.
But in the market, there are lots of different software platforms out there for creating and managing digital twins.
Each one is designed for a different industry and type of application. Some of the top platforms out there include.
Siemens Digital Industries Software
Siemens Digital Industries Software has got you covered with a wide range of digital twin solutions that fit the bill for the entire product lifecycle, from initial design through to manufacturing and operations.
Siemens’ approach is all-encompassing. They integrate multiple engineering disciplines and use IoT data to guarantee real-time precision and functionality.
IBM Watson IoT
What makes IBM Watson IoT stand out is how it brings AI and IoT together to create solid digital twins.
The Watson IoT platform is great for predictive maintenance and operational efficiency. It analyzes data from physical assets and provides actionable insights.
This helps businesses run their operations more efficiently and spot potential issues before they become problems.
PTC’s ThingWorx
PTC’s ThingWorx is known for being flexible and scalable, which makes it great for a wide range of applications, from industrial machinery to consumer products.
ThingWorx makes it easy to develop and manage digital twins by integrating with lots of different IoT devices and data sources, so it’s a great tool for a wide range of industries.
Dassault Systèmes’ 3DEXPERIENCE
Dassault Systèmes’ 3DEXPERIENCE platform is great for creating detailed virtual models of complex systems and products, especially in the aerospace, automotive, and life sciences sectors.
The platform has all the tools you need for simulations and collaboration, so you can create models of products and systems that are really detailed and accurate.
Future Trends and Innovations
One of the most impactful changes will be the rise of advanced AI and machine learning. We’re expecting these technologies to give digital twins a big boost in terms of predictive capabilities.
AI can analyze tons of data to spot patterns and make decisions based on what it finds in real time.
Louise Anderson from Commonwealth Bank points out how AI can transform digital twins by making recommendations and predicting future scenarios with greater accuracy.
Another big trend is edge computing. This tech processes data right where it’s needed, which makes digital twins much more responsive and efficient.
This is especially useful in situations where you need to make decisions in real time, like in manufacturing and logistics.
We’re also going to see a big change in digital twins thanks to the adoption of 5G connectivity. 5G technology will support the continuous updating and real-time interactions that digital twins require thanks to its faster and more reliable data transmission.
To understand DTs’ challenges, you can read “Don’t Get Blindsided: A Playbook at Digital Twins Challenges and Solutions“
Blockchain technology is another promising way that digital twins might evolve.
Blockchain helps keep data safe and reliable, which builds trust and encourages collaboration across industries.
Then, the combination of virtual reality (VR) and augmented reality (AR) with digital twins is opening up new possibilities for immersive training and planning environments.
As David Francis shows in his report for the Australian Meat Processor Corporation (AMPC), these technologies let stakeholders interact with digital twins in more intuitive and impactful ways.
With all these new technologies, we at Interscale offer a set of Building Information Modeling (BIM) and digital twin integration for you.
So, what do we do with all this? We’ll create a comprehensive virtual model to help you manage your projects more effectively and boost your operational efficiency.
Take, for instance, our work with K2LD Architects. It shows what we can do when we put our minds to it—delivering BIM solutions that are just right for the job.
This collaboration has helped make architectural processes more efficient, improve collaboration, and get better results for K2LD Architects.
If you want to know more about how we’re dedicated to your project’s success, kindly visit our Interscale BIM Management Service Support page.
We’d also be happy to set up a one-on-one meeting to discuss your specific needs and how we can help make your project a success.
In Closing
As technology keeps moving forward, digital twins will become a bigger part of our lives, and they’ll help advance various sectors.
But you should know that in practice, it’s not as simple as the theory above suggests.
You need a supporting system provider to stay competitive and achieve operational excellence in today’s digital landscape.
If you try to embrace digital twins technology without a solid supporting system, you’ll end up spending a lot of time and energy on it, which might distract you from your main business.
