What Is a Digital Twin? Definition, Types, and Uses

Written by Coursera • Updated on

Virtual reflections of real-world objects have become increasingly important to many businesses. Read on to find out more about this exciting technology.

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Digital twins are virtual reflections of physical objects used for modeling purposes. While the concept might sound like something out of a science fiction novel, the truth is that digital twins are not only in use today but are actually becoming more widely adopted every year. 

In this article, you’ll learn more about what digital twins are, the different types of them in use today, how they’re used in the real world, and their benefits for businesses. 

Digital twin definition 

A digital twin is a virtual representation of a real-world object or system used to digitally model performance, identify inefficiencies, and design solutions to improve its physical counterpart.

Unlike simulations, which operate in entirely virtual environments divorced from the external world, digital twins model specific real-world assets outfitted with sensors that continuously update their virtual counterparts in real-time with granular, high-quality data. 

Businesses and organizations use digital twins to design, build, operate, and monitor products throughout their lifecycle. Equipped with up-to-date data on physical objects, digital twins can be paired with AI and machine learning to create detailed predictive models and forecast more accurate outcomes than most simulations. 

Digital twin examples 

Digital twin technology is expected to grow exponentially in the near future due largely to the expansion of the Internet of Things (IoT), AI, Extended Reality (ER), and Cloud computing [1]. Nonetheless, it has already been adopted in many industries, which employ it in everything from product design to manufacturing and maintenance.

Here are some examples of how the digital twins are used in the real world every day:  


Manufacturing is a complex industry that requires significant product research and development (R&D), the sourcing and transportation of raw materials through global supply chains, and the physical construction of products through manual and automated labor. The complexity of manufacturing makes it an ideal industry for implementing digital twins, which can help manufacturers improve efficiency and lower costs in nearly every step of the process. 

For example, engineers at an automotive company might use digital twins to model and test prototypes in the early stages of developing new car parts. After modeling prototypes in different simulations, they might then refine the design until settling on a final product. Next, analysts might then employ digital twins to model and subsequently improve the supply chain and manufacturing process required to make the final product before production actually begins. 

Health care 

Data-driven technologies have radically transformed the health care industry in only a few decades. Whether it's used in biomedical engineering, health care analytics, or health care administration, digital twinning has the potential to provide personalized treatments for individual patients, model treatment courses, and assist in the development of novel medical devices. 

But, perhaps the most common way digital twins can be used in health care is through their ability to monitor, manage, and improve physical health care facilities like hospitals. Using digital twins, health care providers can model the day-to-day duties of their staff and the availability of critical resources, such as hospital beds or ventilators, to improve patient care and their overall organizational efficiency. 

Read more: Digital Health Explained: Why It Matters and What to Know

Digital twin types 

Digital twins are capable of modeling everything from individual components to entire systems. While every type of digital twin fundamentally does the same thing – virtually modeling a real-world object or system – their purposes and scope greatly vary between one another. The four primary types of digital twin are: 

Component twins 

Component twins are digital representations of an individual part of a system or product, such as a gear or screw. Rather than simply modeling all the individual parts of a product, though, component twins are typically used to model integral parts, such as those under particular stress or heat. By digitally modeling these parts and subjecting them to dynamic simulations, designers and engineers can see how the parts can be improved to ensure their integrity in likely scenarios. 

Asset twins 

Asset twins, also called product twins, are virtual representations of a physical product rather than its individual parts. While asset twins can technically be composed of numerous component twins, their purpose is to understand how their various parts operate together within a single real-world product. For example, a wind turbine might have an associated asset twin used to monitor its performance and identify possible parts failure due to common wear-and-tear. 

System twins 

System twins, also called unit twins, are virtual representations of systems of products working together. While asset twins model real-world products comprised of many parts, system twins model these individual products as components of a larger system. Understanding how assets interact with one another offers the opportunity to improve how they relate to one another, increasing productivity and efficiency as a result. 

Process twins

Process twins are digital representations of systems working together. For example, while a system twin might model a manufacturing line, a process twin could model the entire factory all the way down to the employees operating the machines on the factory floor. 

What are the Business Advantages of Digital Twins?

Digital twin benefits 

There are as many benefits to using digital twins as there are applications for them.  However, some of the most common benefits of using them include: 

  • Lower overall costs by designing, testing, and refining products or systems in virtual environments before mass production or roll-out. 

  • Improve operational efficiency by modeling systems with up-to-date information, testing alterations in dynamic simulations, and ultimately implementing real-world changes. 

  • Provide swift maintenance to physical assets and existing systems, such as buildings or jet engines, by continually monitoring their performance and identifying issues when they first arise. 

  • Improve the customer experience when purchasing a product or entering a retail outlet by virtually modeling their customer journey. 

Digital twin software

Digital twins are becoming more widely adopted across many industries. To create digital twins, these industries use specific software that allows them to run the complex monitoring required. Some of the most popular digital twin software include:  

  • Azure digital twin 

  • IBM Digital Twin Exchange 

  • AWS IoT TwinMaker

Learn more about digital twins

As novel technologies, such as cloud computing and the Internet of Things (IoT), become more common so too will the importance of digital twins in the work world.

Stay ahead of the curve by learning more today through online flexible courses, such as the University of Michigan’s Digital Technologies and the Future of Manufacturing Specialization. There, you’ll learn more about the Industrial Internet of Things (IIoT), additive manufacturing, and – of course – digital twins. 



Digital Technologies and the Future of Manufacturing

Emerging Digital Technologies in Manufacturing. Learn about breakthrough digital technologies in manufacturing and the business value they deliver.


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Article sources

1. Fortune Business Insights. “The global digital twin market size is projected to grow from $6.75 billion in 2021 to $96.49 billion by 2029 at CAGR of 40.6% in forecast period, 2022-2029,  https://www.fortunebusinessinsights.com/digital-twin-market-106246.” Accessed October 28, 2022. 

Written by Coursera • Updated on

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