Applications of the metaverse in industrial settings are rising steadily, including its increasingly important relative, the digital twin. Many definitions for digital twins exist, but Venture Beat and Gartner offer workable overviews.
Venture Beat proposes that “a digital twin synchronises the data between the natural world and the digital environment (the twin), allowing people to take actions and make decisions in the virtual environment that can be quickly manifested in the real world”.
For analyst firm Gartner, a digital twin is “a databased representation of a physical object or phenomenon that enables the use of virtualisation technologies and algorithms to develop a better understanding of and dynamics between objects and phenomena”.
At the most basic level, a digital twin is a representation of real-world phenomena or objects that captures metrics of interest accurately to improve understanding of the phenomena or objects and offer decision support. Such systems are perfectly suited for planning and design tasks.
Preferably, such digital twins also reflect changes in the real world in real time to always represent the current state of the real-world twin. In this case, data capture systems are necessary that can include sensors, cameras, microphones and so on. Real-time digital twins enable advanced monitoring applications to guide operational tasks.
Finally, digital twins can also find use in control and operations if changes to the virtual representation also result in related changes to the real-world object or system.
Digital twins and the real world
Digital twins can involve the virtual representation of parts or components, equipment, systems or units, and processes that visualise the interplay of systems within an entire production facility, across urban environments, and ultimately on our planet. Furthermore, digital twins can relate to entire supply chains or company activities, and can reflect crucial aspects of entire industries, regions and environmental systems.
The various layers and sections of digital twins can offer important support for commercial, economic, societal and political decisions. “Such twins can range from advanced compounds and bioreactors to the human body and medical applications to manufacturing facilities and urban environments to the entire global environmental ecosystem and climate-change dynamics,” suggests Gartner.
The various types of digital twins have different use cases and purposes, but over time, they will support each other and even develop synergistic relationships as required technologies advance and applications expand. Some of these applications are well understood and already commonly implemented. Other use cases are visions for the future that require comprehensive data input – and therefore substantial data capture and networking infrastructures – and computing power and models that will take many years to establish.
Many experts see real-time updates and representations as a crucial part of digital twins. No doubt, real-time visualisations widen the field of applications. Flexible manufacturing processes, remote operations, and asset monitoring and performance assessment will require real-time updates. Some of these applications will even require extremely low latency to enable safe and effective use of tools and systems.
For comms tech leader Nokia, digital twins are effectively bridges between the physical and digital world. “They accumulate data over time about the structure of a system, its operation and the environment in which it operates, and this data can be used to build intelligence on top using analytics, physics and machine learning,” it says. “It therefore becomes possible to query the digital twin of a specific system and ask about its past and present performance and operations, getting early warnings and predictions and improving productivity.”
Preferably, such digital twins present changes to the system in real time, but even time-delayed representation and visualisation can be insightful – for instance, for disaster analysis or scientific investigations. Even static representations – if comprehensive and detailed – can provide meaningful applications for users and decision-makers.
The back story of digital twins
The history of digital twins goes back further than many might realise. Nasa developed the idea of a digital twin in the 1960s, having created a “living model” of the Apollo mission. This model enabled the ground crew to analyse the 1970 Apollo 13’s near-terminal accident, which the eponymous movie portrays.
Engineers were able to simulate what had happened – an oxygen tank exploded – to evaluate the failure and consider potential remedies to help the crew get home safely. The team simulated the occurrences in computers, but also looked at a physical twin – a replica of the spaceship – to explore potential solutions.
According to Nasa, this “digital twin” was the first of its kind, allowing for a continuous ingestion of data to model the events leading up to the accident for forensic analysis and exploration of next steps. The agency continues to improve digital models, with recent developments discussed in Digital twins and living models at Nasa.
The agency outlines benefits that go well beyond initial planning and emergency evaluations and points to the growing relevance of digital twins as engineering and construction projects increase in size and scale. “The importance of digital twins is increasing as we seek alternatives for certification of structures so large that they cannot be fully evaluated in existing test facilities and autonomous systems that are not deterministic,” it says.
Another example is the Microsoft Flight Simulator series, which started in the early 1980s. Matthew Ball discusses the simulation as an early metaverse example in his book The metaverse and how it will revolutionise everything. Newer versions of Flight Simulator provide increasingly realistic and real-world representations of authentic flight paths, landscapes and airports.
The relationship between professional and gaming digital twins will become increasingly intertwined. Realistically, industrial uses and entertainment purposes of digital twins will influence each other and eventually even merge for a variety of applications.
The many benefits of digital twins
Virtual replicas of systems and processes can support teaching and learning, guide thinking and improve understanding. In education settings, representations of complex systems already find use for medical or engineering students. Simulations of processes enable users to gain an understanding of underlying dynamics and to provide insights about outcomes. This capability is one of the reasons for current efforts to develop digital twins of Earth to investigate climate change and project effects.
Research and modelling will benefit from increasingly accurate representations, with constantly improving granularity. Such models will help in biological studies for protein research and vaccine development. Representations of the human anatomy allow physicians to prepare and train surgeries and procedures by using patients’ data and their anatomy.
Combining realistic virtualisations of systems and components with advanced modelling and design tools offers new possibilities for product developers, system designers and network planners. Prototyping will become a very efficient and effective process, with changes to the model possible at the click of a mouse.
Collaboration of team members and experts across time zones is another advantage of objects in the metaverse. Related, progress documentation, for instance in construction, is almost a byproduct of the ongoing design and planning work. Consumer products, engine components, entire facilities (including related operations and logistics), infrastructure networks such as traffic arteries and sewer systems, and even complete urban environments will see reflection in the digital realm. Such digital twins then can serve engineers in the real world.
“Freed from the drafting room, city engineers could roam the streets with extended reality (XR) glasses,” notes Nishant Batra, chief strategy and technology officer at Nokia. “Looking at intersections through this metaverse lens, they would immediately see how moving a bus stop or adding a traffic light would impact traffic. Proposed changes would then be aggregated and uploaded into a city-wide digital twin, which central planners could interact with in virtual reality.”
As more and more digital twins are created, the number of use cases will grow, as building information modelling combines with assembly-line machinery data and logistical operations, for instance. As the wealth of information grows, the use of digital twins for managerial decision-making will become the norm. When such visualisations take real-time data feeds into consideration, living representations will emerge that enable ongoing monitoring, predictive maintenance, and instant adjustments of processes and operations. More sophisticated representations of facilities, even neighbourhoods, will help planners advance sustainability goals by investigating the effects of new constructions on the environment.
Similar to the way Nasa looked at the events of Apollo 13, digital twins can support disaster analysis and preparation for repairs, evacuations, or whatever else might be necessary. Digital twins will become increasingly crucial tools in situations where access to the area is difficult or requires time not available. Underwater pipelines, earthquake disaster areas, or industrial accidents will benefit from instant access to three-dimensional representations, potentially real-time data and simulation capabilities.
In addition, post-analytics of disasters for future accident prevention will benefit by feeding available data – such as from aircraft black boxes or industrial monitoring sensors – into models for further investigation. And digital representations can make use of rapidly advancing machine learning and artificial intelligence.
Another crucial aspect of digital twins is the ease with which they can integrate the wide range of existing data repositories. The opportunities that emerge when these twins connect will be substantial – the whole is greater than the sum of its parts.
Martin Schwirn is the author of “Small data, big disruptions: How to spot signals of change and manage uncertainty” (ISBN 9781632651921). He is also senior advisor for strategic foresight at Business Finland, helping startups and incumbents to find their position in tomorrow’s marketplace.