The concept of digital twin dates back nearly three decades, to the 1990s. However, the emergence of new technologies such as AI, machine learning and predictive analytics, have expanded the use of digital twins beyond its original intended usage of manufacturing and engine design.
Today, it is quickly expanding to take on various forms across industries, enabling companies to forecast and create with more accuracy and foresight. It may even hold the key to the success of the metaverse.
A Long Way in the Making
Truth be told, the concept of digital twins dates back to well before the 1990s. NASA had used physical replicas of spacecraft for simulations as early as the 1960s. But it's really only in 1991 that the concept of digital twin technology was initially discussed in David Gelernter’s book "Mirror Worlds."
It would then take 10 years for Michael Grieves, then with University of Michigan, to apply the concept of digital twins to manufacturing and introduce digital twin software in 2002. In its 2018 Top 10 Strategic Technology Trends report, Gartner predicted that digital twins would soon exist for billions of things, potentially saving billions of dollars in maintenance repair and operation (MRO) and optimized IoT asset performance.
What Exactly Are Digital Twins?
The term digital twin refers to a virtual representation of a physical object, product, service or system that spans its lifecycle, is updated using real-time data and helps inform decision-making through the use of simulations, machine learning and reasoning. With Web3 and the metaverse on the horizon, the use of digital twins has expanded to include buildings, factories, cities, people and processes, extending the concept even further.
According to Accenture’s Technology Trends 2022 report, the global digital twin market was valued at $3.21 billion in 2020 and is expected to grow to $184.5 billion by 2030. Accenture forecasts organizations will use digital twins to invent products, design experiences and run their businesses in completely different, innovative ways.
IBM breaks down the concept of digital twins into four types, each based on the level of product magnification:
Expanding Possibilities
The applications of digital twins are constantly expanding.
"In this year’s Vision, we note the example of Vail Ski Resort, which is using a digital twin to monitor real-time weather conditions, snowfall, optimize positions of the snow guns, all to improve ski conditions to be more dependable and predictable," said Michael Biltz, managing director at Accenture Technology Vision. "We’ve also talked about the Port of Rotterdam which has built a digital twin that tracks ship and container movements and is being used to optimize operations."
Several platforms available today enable organizations to design and create digital twins. Microsoft Azure Digital Twins, for instance, is an Internet of Things (IoT) platform that enables the creation of digital representations of real-world things, places, business processes and people, including buildings, factories, farms, energy networks, railways, stadiums and even entire cities.
NVIDIA's Omniverse facilitates collaboration on 3D design, the creation of digital twins and the development of multi-app, multi-user simulations. NVIDIA describes Omniverse as “an easily extensible platform for 3D design collaboration and scalable multi-GPU, real-time, true-to-reality simulation.” The platform enables organizations to create physically accurate virtual replicas of objects, processes or environments, which are then continually synchronized with AI-enabled real-world data.
“Digital twins give an enhanced virtual, real-time and AI-driven model of applications, systems or objects in the enterprise, and, as such, hold tremendous potential for efficiencies, improvements, product development, market-entry, customer engagement — really, anything that an enterprise does,” said Gary LaFever, CEO and general counsel of Anonos.
Real World Applications of Digital Twins
Many organizations already use digital twins, including the Food and Drug Administration. “Some examples include NTT’s work last year to build a digital twin for the Tour de France and the Living Heart Project, a collaboration between Dassault Systèmes and the FDA, which is using digital twin technology to revolutionize cardiovascular science,” said LaFever. “We can expect an exponential rise in digital twin projects.”
Another example comes from digital twin service provider UrsaLeoa, which partnered with the Active Building Centre and the UK government on a decarbonization and energy optimization project. By using a digital twin of sites and buildings, they are able to measure what is occurring (i.e., temperature, humidity, energy consumption) on a real-time basis and can, therefore, better understand the dynamics and make informed decisions. Lights and temperature, for example, can be configured to automatically reduce usage based on the time of day or when people are present. Digital twins are able to be connected to solar panels, heat pumps, plumbing systems and other systems in order to optimize energy use and reduce greenhouse gasses.
Where Digital Twins Fit in the Metaverse
A generic example of a digital twin and how it’s used is that of an engine outfitted with sensors related to its various areas of functionality. The sensors generate data about the aspects of the engine’s performance and conditions. That data is then passed on to a processing system that applies it to the digital twin of the engine. Once the virtual model is informed using the sensor data, it can be used to run very accurate simulations, study inadequacies or problems, and generate potential solutions or actions that should be applied to the physical engine.
The ability to run accurate simulations extends to the metaverse, where they can be applied to interactions with virtual users. "Ultimately the metaverse is the connective tissue that binds lots of different worlds together, while the digital twins may come to represent the worlds (or part of the worlds) themselves," said Biltz.
"Imagine you have someone who works at the port or in a manufacturing plant. They want to monitor a machine, order new parts or materials, and then go catch up with their co-worker about their next project. Today, these interactions are distributed across a dozen different systems. With digital twins, some of these interactions get further consolidated into a single point but still stand in isolation. With the metaverse, someone would be able to seamlessly have all these interactions, then jump over to another world and engage over there," Biltz said.
Digital twins are a core element of the metaverse because they digitally represent the physical world and enable users to interact with the digital versions of people, places and things from any location. “The appeal of the metaverse is bringing as much of the real-world environment into a virtual system. The interactions between virtual machines, systems and infrastructure must be realistic in appearance and functionality — and the best way to do that is by modeling these components using digital twins," said Brad Hart, CTO of version control at Perforce Software. "The game engines are used today to build modern digital twins have built-in physics simulation/logic to accurately mock their real-world counterparts, which is key to the metaverse's success."
Future-leaning organizations are cautiously beginning to get a foothold in Accenture’s Metaverse Continuum, which hosts multiple virtual worlds that facilitate many varied experiences, with the goal of reshaping how people interact and work. For instance, Mars is working with Microsoft and Accenture to utilize digital twins to reduce waste, increase speed and capacity, and enable its workers to make real-time decisions across its supply chain. The company is now adapting this concept to product development by using digital simulations which incorporate variabilities such as climate and disruptions while observing other details in the product lifecycle.
Potential Roadblocks
According to Puneet Saxena, VP of supply chain planning at Blue Yonder, one of the potential roadblocks for the effective use of digital twins is that these initiatives are data-intensive and that it is challenging to secure clean and complete data. “Over the past two decades, however, more and more companies have been investing in building robust data management processes and governance models that allow reliable data within the enterprise to be available more readily,” said Saxena.
LaFever said another challenge is data privacy because data twins require more complex and larger amounts of international data. “Taking the issues that Facebook is having under GDPR as an example, compliance with data from different global areas is tricky. For Facebook, the issue is the fact that when the European data goes to the US, it is processed into unprotected cleartext when in use, in violation of GDPR requirements. This cleartext data is needed for processing because protected data is not as accurate,” he said.
Final Thoughts
Digital twins are used across a variety of industries, from retail to pharmaceuticals, to green energy and climate change. It has become a tool for creating enhanced virtual, real-time and AI-driven models of applications, systems or objects in the real world.
The technology is also being used to bring much of the real-world environment into the virtual system known as the metaverse. As organizations continue to recognize the value of digital twins, we can expect the use of digital twins to evolve and grow.
This article originally appeared in CMS WiRE. All trademarks are the property of their respective owners. All rights reserved by the respective owners.
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