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The Rise and Rise of Digital Twin Technology
The Rise and Rise of Digital Twin Technology

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Digital Twin – Trending Since Early 2022

Google search term analytics reveals an interesting trend for the term Digital Twin and the related terms of virtual twin, digital thread, industry 4.0, and digital manufacturing. While Industry 4.0 was searched the most between late 2018 and end of 2020, digital twin started gaining momentum as a search term from the start of 2020 and overtook Industry 4.0 by early 2022. In the family of terms that most commonly represent digital/remote maneuvering of physical processes, operations, and systems, Digital Twin is now the most trending term.

 

Digital Twin, Virtual Twin, Digital Thread, Industry 4.0, Digital Manufacturing – Google Search Trends, October 2018-2023

 

 

Another interesting trend that comes up when analyzing each of these terms and the regions with most search hits between the same time as above is that most advanced economies that have already responded to the 2011 Industry 4.0 revolution, show higher inclination towards digital twins now. In India, for instance, 56% of the search hits are on Industry 4.0, only 25% on digital twins, versus, a USA where 45% are on digital twins and 29% on Industry 4.0. However, increasingly experts believe that an optimal Industry 4.0 implementation, and its logical extension to an industrial metaverse, entails digital twin by design.

 

 

Origin of Digital Twin

The term Digital Twin was first introduced in a David Galernter book, “Mirror Worlds,” that anticipated a world with mirrored physical entities, in virtual space, and a time when nearly every physical entity would have a digital cousin. The concept and model of digital twin was first made public by Michael Grieves in 2002 at a Society of Manufacturing Engineers conference in Troy, Michigan where digital twins were considered as the underlying conceptual model of a product over its lifetime, thus aligning digital twins with product lifecycle management or PLM. In earnestness, NASA’s Apollo 13 mission rescue back to Earth safely after an onboard explosion that led to aborting of the moon landing mission, is considered one of the, if not the, finest examples of practical digital twin application. It involved on-ground simulation and real-time ground-spaceship communication.

 

Digital Twin is the conceptual design and dynamic virtual model of the physical.

 

The physical entity can be the smallest independently identifiable component, a product, a system of products, a system of systems, or a process. Digital twin combines the physical, the digital, and the connectivity between the physical and digital at a certain frequency and fidelity to ensure that the digital replicates the physical as closely as possible. The objective is to optimize the performance of the physical by analyzing and predicting workings on a digital copy.

 

 

Current Digital Twin Market

Traditionally, digital twin technology was considered relevant for application in sectors or use cases where the cost-benefit of virtualization was seen from the perspective of physical risk intensity or inaccessibility (the Apollo 13 mission). Aerospace and defense stood out in its use of digital twin in its earliest days. However, since then, it has been recognized that performance prediction, optimization, and enhancement are objectives that can be well-achieved with digital twin technology.

In the past decade, manufacturing has emerged as the largest adopter of digital twin technology, currently at a global spend of nearly USD 6-6.5 Bn. There are multiple promising projections about the global spending growth in digital twin technology through 2030, at CAGRs ranging between 35% to 65%! According to a 2022 study by IoT Analytics, nearly 30% of global manufacturers have fully implemented or are implementing digital twin strategy, and another 63% are developing one.

 

 

Digital Twin Elements – Strategy and Technology

It might seem that digital twin is the ultimate answer to every physical problem of predictive monitoring and management. However, experts concur that digital twin is not the right solution to every such problem. A digital twin strategy, therefore, requires assessment of its sustained long-term value addition. Many of these strategy elements were not well-studied before the pandemic, but post-2020, the unprecedented digital push particularly in getting enterprise data in order and thinking through technology convergence has brought forth a cohesive digital twin strategic approach:

 

 

The strategic approach underscores the salience of technology convergence in making digital twins work – computing infrastructure, sensing and control technology, network communication tech, process and display modeling and simulation, enterprise data strategy, analytics and intelligence, and human-computer interface technology, and lately, the metaverse.

 

 

Tailwinds Driving Digital Twin Adoption

One of the most sophisticated functioning digital twin implementation is that of the Singapore city-state. Started in 2014 as part of its Virtual Singapore smart city initiative, it was finally implemented as a 1:1 3D scale model in mid of 2022. The objective is to make Singapore future-ready against environmental risks and to do so sustainably. An amazing achievement as part of this initiative was the actual 3D modeling that was completed within two weeks! This was however a result of multiple ongoing initiatives since 2014 – sensors across the city, a country-level data strategy, an immersive smart city experience model built since 2014 for citizens to experience, high-resolution LEO satellite images, and synthetic image modeling using AI.

 

There are multiple technology tailwinds that will continue to drive-up digital twin adoption in the next 5-7 years:

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As we further explore Digital Twin technology, stay tuned to read about the technology components and types of digital twin use cases in focus in 2023.

 


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Namita Jain
Deputy Director, Research

Researching technology for actionable impact since my 12 years in tech strategy and advisory

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