What is a digital twin, and how does it work?

Key takeaways

• A digital twin isn’t just a digital lookalike of physical assets; it behaves like the real thing, reflecting everything from how a machine operates to how a city functions, all in real-time.
• Whether it’s in manufacturing, smart cities, healthcare or even space exploration, digital twins are being used to optimize processes, improve efficiency, and reduce risks across various sectors.
• Creating a digital twin involves collecting massive amounts of data and using sensors to continuously feed real-time information back to the digital model, ensuring it accurately mirrors its physical counterpart.
• The concept of digital twins isn’t new, but it’s constantly evolving. As technology advances, digital twins are becoming even more integral to how industries operate, pushing the boundaries of innovation and efficiency.

A digital twin has been an intriguing concept in the tech space for some time. If you’ve ever wished for a way to have a perfect virtual copy of something in the real world — a machine, a building or even an entire city — then a digital twin is exactly the same. 

These virtual models don’t just look like their physical counterparts; they act like them, too. It’s like having a mirror that reflects not just appearances but behaviors, conditions and all the little details — in real-time.

If you’re curious about how things tick in digital twin technology, how it functions, and why it has become such a big deal across industries, this article will break it down for you. It will explain how a digital twin is made, the types of digital twins, the benefits and risks of digital twins, use cases of digital twins, and the history of digital twins.

Digital twin, explained

A digital twin of an item, process or system is like a virtual copy of the real thing. Think about having a digital copy of a plant, a car or a city on your computer. This digital twin acts exactly like the real stuff, allowing you to experiment with different situations virtually. 

You can anticipate potential issues and optimize performance without interacting with the physical version. For example, engineers can use a digital twin of a jet engine to simulate how it would operate under various conditions without needing to use the actual engine.

A digital twin works effectively, thanks to the continual feed from its physical peer. It could be used in diverse applications, such as smart cities, healthcare, industry research and space research.

How is a digital twin made?

Here’s how it all starts. You gather tons of data about the asset: the way it looks, how it behaves under different conditions, and how it interacts with the stuff around it. You create a digital version that’s pretty much a replica of the original asset.

But it doesn’t just stop at appearances; this digital twin behaves like the real thing, too, due to technologies like augmented reality (AR), virtual reality (VR), 3D modeling, artificial intelligence and the Internet of Things (IoT). You then connect the real asset with sensors that send data back to the digital twin in real-time. 

This way, you can monitor and analyze everything constantly through a cloud-based platform. The result? A digital twin that mirrors the real-world asset.

Did you know? AI can generate realistic scenarios within digital twins, allowing us to test self-driving cars or medical treatments without real-world risks.

How does a digital twin work?

Wondering what a digital twin does? It depends on how much data you feed it and what you want it to do. For example, do you just want it to keep an eye on an asset, or do you want it to go further, like spotting issues before they happen and suggesting fixes? 

Typically, these digital twins are designed to monitor a physical object, analyze its performance, and adjust as needed. Engineers keep the digital twin updated with real-world object data to simulate what’s happening in real-time and offer insights. This way, potential problems are spotted early on before they become big issues.

Digital twin example: Volvo

Let’s understand this concept with an example. Volvo, the Swedish automobile company known for its focus on passenger safety, uses digital twins to create virtual replicas of its buses and trucks, allowing it to test different materials and designs. 

Imagine sensors embedded in a prototype vehicle monitoring everything from how it holds up structurally to how it handles aerodynamics and safety during crash tests. All this data flows into the digital twin, which simulates how the car would perform in various situations, like speeding down a highway or handling a collision. 

Volvo’s engineers can then tweak the design, pick the best materials, and optimize performance and fuel efficiency by using the digital twin. Volvo can test new safety features in this virtual space before rolling them out in the real world, reducing the risk of costly mistakes and ensuring top-notch safety for the passengers.

Types of digital twins

There are different types of digital twins, each with its own role:

• Component twins or parts twins: Think of these as the building blocks of a system. They’re the smallest yet most essential parts.
• Asset twins: Combine a few components, and you’ve got an asset. The asset twins help monitor how these parts work together and show where you can make improvements.
• System or unit twins: These let you see how different assets work together to form a whole system, helping you understand the interactions and find ways to boost overall performance.
• Process twins: At the highest level, process twins give you a big-picture view of how entire systems interact within a larger operation, like a factory. They’re crucial for ensuring everything runs smoothly and efficiently.

Comparing digital twin vs. simulations

Even though they sound alike, a digital twin and a simulation aren’t the same. Simulations offer the ability to test scenarios within a controlled environment, but a digital twin expands upon this capability. It is a live, real-time digital copy in sync with the real one and provides real-time information. You can think of a digital twin as much more powerful and live simulations. 

This table sums up how digital twin and simulation compare to each other:

Benefits of digital twin technology

Digital twin technology offers many benefits, including:

• Cost savings and risk management: Digital twins allow companies to save money and manage risks by performing virtual simulations and testing instead of relying on physical prototypes. This reduces the costs and potential dangers associated with product development.
• Improved R&D efficiency: Digital twins facilitate more effective research and development by providing a platform for virtual product testing. Companies can gather detailed data on product performance and make necessary adjustments before moving to physical production.
• Production optimization: Digital twins help optimize production processes by monitoring operations in real-time. They enable companies to identify inefficiencies and make adjustments quickly, ensuring that production lines run smoothly and efficiently.
• Sustainable end-of-life management: When products end their life cycle, digital twins help manufacturers determine how to recycle or repurpose materials effectively. This reduces waste and supports sustainability efforts.
• High-quality production: Digital twins contribute to higher product quality by allowing companies to detect and address defects early in production. This proactive approach ensures that the final product meets quality standards and reduces customer complaints.

Risks of digital technology

Like every other technology, digital twins, too, have their share of possible risks, such as:

• Data security issues: With so much data moving back and forth between the physical item and its virtual counterpart, there is the risk of this data passing into the wrong hands. Cybersecurity becomes highly important in this scenario.
• High implementation costs: Creating a digital twin is costly. Smaller businesses may find it difficult to afford the initial investment due to the high cost of the software and the sensors.
• Data overload: It’s possible to become overwhelmed by the volume of data that’s being received. An abundance of information can cause analysis paralysis by making it difficult to concentrate on what matters most.
• Dependence on accurate data: A digital twin’s efficacy is dependent on the quality of the data it is fed. Decisions made based on inaccurate insights can be inaccurate.
• Complexity of integration: Digital twin integration with existing systems can be a challenging procedure. If executed incorrectly, it could cause disruptions rather than enhancements to operations.

Use cases of digital twins

Let’s explore some applications of digital twins in various sectors:

• Manufacturing: Manufacturers use digital twins to build virtual representations of their production lines. It helps them to identify bottlenecks, adjust procedures, and even forecast when equipment may break down. This translates into fewer hiccups and more productivity.
• Infrastructure and smart cities: Can you think of a city where everything from traffic lights to water systems is monitored and optimized in real-time? Digital twins allow city planners to do exactly that. It helps them better manage resources, model the effects of new developments, and even plan for crises such as floods or traffic jams.

Did you know? Cities such as Singapore use digital twins to optimize traffic flow and energy consumption, creating smarter urban environments.

• Healthcare: Digital twin technology helps create a virtual representation of a human body part. Medical professionals can use it to test novel therapies, gauge a patient’s reaction to a drug, or even do mock surgeries before performing the actual procedure.
• Automobiles: Automakers use digital twins to test new materials, perform accident simulations, and improve designs without having to construct actual prototypes of vehicles. This expedites the design process of vehicles.
• Energy: Digital twins are employed in the energy sector for the purpose of managing and monitoring assets such as oil rigs, power plants and wind turbines. Businesses may minimize downtime, forecast maintenance requirements, and maximize energy production by modeling the operation of these assets. 
• Defense and aerospace: In aerospace, digital twins help maintain the efficiency and safety of airplanes. Engineers are able to evaluate the fatigue resistance of various materials, simulate flight, and even forecast maintenance requirements by building virtual models of airplanes. This prolongs the aircraft’s lifespan and increases safety.

History of digital twin

The history of the digital twin can be traced back to David Gelernter’s book Mirror Worlds, which was published in 1991. But it was in 2002 when University of Michigan professor Michael Grieves introduced the formal idea of digital twin software. In 2010, the National Aeronautics and Space Administration’s (NASA) John Vickers coined the phrase “digital twin,” which is still used today.

However, the concept of examining a physical object through the lens of a digital twin actually goes back much further. NASA came up with the idea in its space missions in the 1960s. It had this strategy where each spacecraft that was supposed to go into orbit had an exact replica. NASA’s flight crews used this earthbound version to conduct studies and simulations.

Did you know? NASA used digital twins to virtually repair the Apollo 13 spacecraft, proving their life-saving potential even before the term existed.

The future of digital twin

It is quite incredible how digital twin technology has changed the way things work in various sectors. Digital twins have proved to be an effective tool for innovation that can improve manufacturing efficiency, smarten cities, alter the healthcare industry, and more.

As technology develops, the importance of digital twins will only increase, stretching the limits of what you can accomplish in the real world using the digital version. Comprehending digital twin technology will help understand how it will influence the future of how you’ll create, manage and optimize the world around you.