digital twins

These 7 Industrial Sectors Are Seeing Remarkable Results From Digital Twins

October 21, 2021 - Emily Newton

Revolutionized is reader-supported. When you buy through links on our site, we may earn an affiliate commision. Learn more here.

Everything is going digital. Thanks to the rise of data-driven devices and platforms like IoT, machine learning and cloud computing, digital twins have continued to grow in prevalence.

The primary reason for creating and utilizing a digital twin is to inform decision-making using a digital model of a physical object or system. The model uses a significant amount of collected and analyzed data. Thus, the twin can help teams understand, process and sometimes even predict behaviors of an object or system.

People are currently deploying and using digital twins across many sectors like architecture, construction, manufacturing, health care, retail and more. To understand why they’re so powerful and convenient, we must dig a little deeper.

What Is a Digital Twin?

A digital twin is a virtual model or representation of a physical object, system or application. Most digital twin uses involve studying a targeted object. People use the information to make more informed decisions, predict potential outcomes, build an accurate maintenance or service schedule and more.

IBM’s example of a digital twin is an excellent place to start. It describes outfitting a wind turbine with a bevy of sensors related to “vital areas of functionality.” They collect data while the wind turbine operates. The associated data covers performance, energy output, weather conditions, temperatures and other aspects. The data goes to central processing system, and people later apply it to a digital twin — a virtual copy of the turbine.

Said an IBM spokesperson: “Once informed with such data, the virtual model can be used to run simulations, study performance issues, and generate possible improvements, all with the goal of generating valuable insights — which can then be applied back to the original physical object.”

A digital twin is not the same as a simulation. The difference becomes more obvious once you get things working. People can produce and utilize digital twins at scale. That opportunity enables studying and analyzing several complex processes and systems. A simulation typically focuses on one process.

In the wind turbine example, the digital twin analyzes, understands and processes loads of data about its operation, performance, environmental conditions and so on. Digital twins are also much more accurate and representative of the real, physical object compared to virtual simulations.

Digital Twin Applications: Sectors Seeing Remarkable Results

The best way to understand how digital twins work and the many benefits they offer is to see them in action. Many industries use this technology to improve operations and processes. Here are some examples.

1. Manufacturing

There’s no better example of a digital twin application than in the manufacturing industry. Empowering product development, unique design, at-scale personalization, predictive maintenance and more, digital twins revolutionize the industry. The next industrial revolution, or Industry 4.0, is largely fueled by digital and data-driven technologies, including digital twins.

In product development, engineers can test the feasibility of planned or upcoming projects before they launch, even before trials or consumer tests. The results can then fine-tune the products, leading to more successful initiatives.

Similar things can happen with unique design and at-scale personalizations. Designers and project managers can generate potential product variants, whether style or feature changes. Those efforts offer better flexibility for customers. They can even support new opportunities such as manufacturing-as-a-service, which is incredibly important to the future of the industry.

2. Automotive

When people develop and design new cars, they start with digital concepts. This provides a good visual representation of a potential vehicle, but not a viable physical representation. In time, as that vehicle moves forward in the development process, things may need to change based on how it reacts or operates in the real world. Digital twins are being used, increasingly, to speed up and improve this process, especially with connected vehicles — like autonomous or self-driving variants.

Testing vehicles has become incredibly complex, even more so when you’re talking about vehicles that drive themselves sans human input. Digital twins empower that process and help inform future decisions through the support of real-world data. In that way, auto manufacturers now have the tools and technologies to test vehicle concepts before they ever make it onto a testing track or physical roadways.

3. Supply Chain

Because it’s constantly in motion, and thanks to so many strains due to the current climate, there isn’t really an accurate way to test out new concepts, products, or changes to the current supply chain, at least not without creating huge delays.

Digital twins are the answer to this problem, allowing logistics teams to try out various things while also getting an accurate representation of how it would affect operations. They are an integral part of the ever-evolving digital supply chain, too, which is vastly improving operations through technologies like advanced analytics, robotics, automation, rapid manufacturing, and more.

For example, new product packaging or altered designs can be virtualized by running them through a digital twin model, to identify potential problems before they ever make it to market. Teams can use the same tools to understand environmental or shipment conditions, optimize inventories and placement, and more.

Imagine a predictive model that can be applied to nearly any scenario, not just with incredibly accurate results but also those that mirror the real world.

4. Architecture

In the world of architectural design, digital twins are an instrumental albeit relatively new addition to the field. Typically, designers know how a project is going to turn out and they always try to build or create based on various specifications. But there are sometimes curveballs that might force them to alter a design or model beyond what they might want or prefer.

Digital twins can help retain some of those original designs, finding new ways to work around certain limitations, but also providing real-world data to achieve functional concepts. Designers are merging BIM (building information modeling) data with scans and operational data to create incredibly accurate digital representations of buildings or entire communities.

What’s more, architects can work more directly with construction and development crews by leveraging some of the real-world data that digital twins provide. Some of the nuances of past or previous work can help inform future designs, as well as inform creators about some of the requirements or specifications that teams have requested before.

5. Construction

Similar to the other industries, digital twins can help construction crews better plan out projects, and understand how they’re coming along, in real-time. This enables revisions or changes in the moment, creating more optimized structures and projects overall. They can see what is or isn’t going to work, make those changes, and continue with the rest of the project, without delaying the entire build or extending construction times.

The models can also be used to inform future projects, applied to upcoming designs or builds that are currently in progress.

6. Health Care

Digital twins in the health care industry can be used to inform and drive action when it comes to general health care services, and be used to inform research and development, whether you’re talking about medical devices, pharmaceuticals, or something else.

Researchers and health care professionals can’t always take new products, procedures, or strategies and apply them to the human body, at least not without proper testing, because some concepts are just too risky. Digital twins can provide access to real-world data, giving a proper channel to test out those new products or services.

Philips’ HeartModel, the ideal example, creates a highly personalized view of a patient’s heart, based entirely on 2D ultrasound images. It allows health care professionals to build a visual and digital twin of a patient’s heart, to be used for further study. Virtual hearts could very well save lives one day!

Another great example is the optimization of hospital staff and processes to meet fluctuating demands, especially with everything happening because of COVID. Creating a digital twin of those hospital operations can help operators examine performance, problems, and other events, which can be applied in the real world to better prepare and support active facilities.

7. Retail

While digital twins aren’t exactly the same as simulations, they can certainly help in creating them, particularly when it comes to consumer and market modeling. Retailers can use digital twin technologies to delve into products, customer sentiment, behaviors, and more. The real-world data informs action, resulting in better product delivery and customer service.

One company, Pygmalios, invokes Retail 4.0 to vastly improve in-store experiences with the help of real-time and granular data from IoT sensors. Store owners can use the collected information to build real-world maps of traffic, seeing what paths customers are taking through their stores. They can also see information like the average demographic, purchases made, or even overlooked products on shelves and displays.

Digital Twins Are Shaping Our Future

Most digital twin uses, and arguably the best digital twin application possibilities, inform planning and future action. Whether you’re talking about optimized construction operations, better and more accurately designed architectural models, virtual research for new health care products, or one of the many other possibilities, digital twins are shaping our future.

Many industrial sectors are seeing incredible results by deploying and applying digital twins, using real-world data to perfect various processes and operations. As we embrace the digital realm more and more, it’s no wonder something like this would become so prevalent — having a real-world virtual model to extract actionable intel from is invaluable.

Revolutionized is reader-supported. When you buy through links on our site, we may earn an affiliate commision. Learn more here.

Author

Emily Newton

Emily Newton is a technology and industrial journalist and the Editor in Chief of Revolutionized. She enjoys reading and writing about how technology is changing the world around us.

Leave a Comment





This site uses Akismet to reduce spam. Learn how your comment data is processed.