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

Digital twins are virtual reflections of physical objects used for modelling 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 becoming more widely adopted every year. 

In this article, you’ll learn more about what digital twins are, their different types 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 organisations use digital twins to design, build, operate, and monitor products. 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 shortly due largely to the expansion of the Internet of Things (IoT), AI, and cloud computing [1]. 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 digital twins are used in the real world every day:  

Manufacturing 

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 labour. This complexity 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 modelling prototypes in different simulations, they might refine the design until the final product is settled. Next, analysts might employ digital twins to model and improve the supply chain and manufacturing process required to make the final product before production begins. 

Healthcare 

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

However, perhaps the most common way digital twins can be used in healthcare is through their ability to monitor, manage, and improve physical healthcare facilities like hospitals. Using digital twins, healthcare 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 organisational efficiency. 

Digital twin types 

Digital twins are capable of modelling everything from individual components to entire systems. While every type of digital twin fundamentally does the same thing – virtually modelling a real-world object or system – their purposes and scope greatly vary. The four primary types of digital twins 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 modelling 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 modelling these parts and subjecting them to dynamic simulations, designers and engineers can see how they 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 parts. While asset twins can technically be composed of numerous component twins, they aim to understand how their various parts operate within a single real-world product. For example, a wind turbine might have an associated asset twin 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 their relationship with 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, down to the employees operating the machines on the factory floor. 

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: 

• Design, test, and refine products or systems in virtual environments before mass production or rollout to lower overall costs. 

• Improve operational efficiency by modelling 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 arise. 

• Improve the customer experience when purchasing a product or entering a retail outlet by virtually modelling 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 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 flexible online courses, such as the University of Michigan’s Digital Technologies and the Future of Manufacturing Specialisation. There, you’ll learn more about the Industrial Internet of Things (IIoT), additive manufacturing, and digital twins.