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It is normally employed to:

• Monitor the operation of an existing device (like an aircraft
  engine) to predict problems before they occur; or
• Simulate the operation of a new device or product, enabling
  refinements during the design and development stages.

Digital twins make extensive use of sensors deployed in the objects
they emulate – a process rendered cost-effective by leveraging another
emerging technology: the Internet of Things (IoT) or, more specifically,
the Industrial Internet of Things (IIoT).

Digital Twin Market

According to a recent report published by Research and Markets
(“Digital Twin Market: Global Industry Trends, Share, Size, Growth,
Opportunity and Forecast 2022-2027”), the global digital twin market,
valued at $10.3 billion in 2021, should reach $54.6 billion by 2027,
realizing a remarkable compound annual growth rate (CAGR) of 31.7
percent during the period from 2022 to 2027.²

Largely responsible for popularizing the concept, Gartner declared the
digital twin one of the “Top 10 Strategic Technology Trends of 2017.” In
evaluating the technology’s potential, analyst Kasey Panetta predicted a
transformative future. “Using physics data on how the components of a
thing operate and respond to the environment as well as data provided by
sensors in the physical world, a digital twin can be used to analyze and
simulate real world conditions, [respond] to changes, improve
operations, and add value.”³

Already a vital defense industry asset, Figure 1 depicts a US Navy
digital twin in action.

Figure 1. A US Navy Digital Twin In Action

Fran White, left, a
civil service employee at Space and Naval Warfare Systems Command,
Systems Center Atlantic, and Clayton Bush, a Tactical Networks
contractor, work with Petty Officer 2nd Class James Rago to troubleshoot
the video teleconference system of a video information exchange system
aboard the aircraft carrier USS Ronald Reagan.

Source: Navy CIO – Navy.mil

Digital Twin Types

A complex field, analyst Gitanjali Maria has identified three basic
types of digital twins:

1. Discrete digital twins – “Virtual replicas of
   individual products/equipment, persons, or tasks.”
2. Composite digital twins – “Virtual models of
   multi-part systems, such as cars and industrial machines.
3. Digital twins of organizations (DTOs) – “Virtual
   models of complex and large entities (e.g., an entire organization or
   a city), composed of the digital twins of their constituent parts.
   They help monitor and optimize higher-order business performance.”⁴

Digital Twins and PLM

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The concept of a “digital twin” was first articulated by Dr. Michael
Grieves at the University of Michigan in 2002, within the context of a
presentation on product lifecycle management (PLM).⁵ Indeed,
digital twins are ideal in helping to solve a number of product
lifecycle challenges, as itemized by Chris O’Connor of IBM.⁶

Digital twins promise a revolution in product development, helping
ensure that:

• Ill-conceived products are identified early in their lifecycle and
  either abandoned or redesigned.
• Product defects are discovered and repaired prior to production.
• Costs are contained by pursuing a virtual development
  first approach.

Origins of Digital Twins

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Digital twins exists within the wider space of computer simulation and
emulation technologies. Among their technological antecedents are
computer simulation, pairing technology, and computer virtualization.

Computer Simulation

One of the first major advances in computer simulation occurred in 1962
with the creation of SimScript. Even today, the SimScript platform
remains a popular tool for building computer simulation models used in
decision support applications, especially for:

• Military war gaming
• Communication network optimization
• Transportation planning
• Inventory control
• Financial market management

Pairing (or Mirrored) Technology

In the early days of America’s space program, NASA used “pairing
technology” to help monitor and manage distant spacecraft. As analyst
Bernard Marr reveals, “When disaster struck Apollo 13, it was the
innovation of mirrored systems still on earth that allowed engineers and
astronauts to determine how they could rescue the mission. Today, NASA
uses digital twins to develop new recommendations, roadmaps, and
next-generation vehicles and aircraft.”⁷

Computer Virtualization

With computer virtualization, a software-level “hypervisor” partitions
a real server or mainframe into multiple “virtual machines.”
Virtualization technology became popular in the 1970s when IBM released
its VM/370 operating system. Originally intended as a test tool for IBM
engineers, VM/370 permitted a real mainframe to be split into dozens of
virtual machines, each capable of running an IBM operating system such
as SVS, MVS, DOS, and CMS.

Virtualization technology (server, storage, desktop, and network),
allows the development of virtual (or software-defined) data centers
which can reduce an enterprise’s overall IT spend.

Digital Twin Applications

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Digital twins may be used to satisfy a variety of enterprise business
and technical needs, improving operations, lowering costs, and achieving
new capabilities.

Sector Penetration

Digital twins are presently experiencing some of their greatest growth
in the following industries:

• Manufacturing – Improving shop floor performance and enabling
  predictive maintenance.
• Healthcare – Enhancing operational efficiency and improving
  personalized care.
• Supply Chain – Optimizing warehouse design and predicting the
  performance of packaging materials.
• Construction – Understanding how a building is performing in
  real-time.
• Automotive – Designing new cars and vehicular accessories.⁸

Smart Manufacturing

The US National Institute of Standards and Technology (NIST) is
promoting digital twins as “an important concept for achieving smart
manufacturing,” and has identified three potential smart manufacturing
use cases: the Machine Health Digital Twin, the Scheduling and Routing
Digital Twin, and the Virtual Commissioning Digital Twin.

Machine Health Digital Twin – A
machine health digital twin can use process and equipment data to
monitor, troubleshoot, diagnose, and predict faults and failures in
manufacturing equipment. Through using process and equipment data, a
digital twin can generate actionable recommendations for the users or
deliver control commands to control the equipment. A machine health
digital twin may include the following functionalities:

1. Define maintenance objectives and goals,
2. Collect maintenance and performance measurement data,
3. Analyze collected equipment status data, and
4. Generate control commands or actionable recommendations.

Scheduling and Routing Digital Twin –
To respond to the market demand for more customized products,
manufacturing systems need to be more flexible to produce different
products using the same resources. This includes routing flexibility and
machine flexibility, i.e., an operation can be executed in more than one
machine or a machine can perform more than one operation for resource
sharing. A scheduling and routing digital twin can collect data from
shop floor systems such as production equipment, MES, and ERP systems to
analyze the current status of the production system for identifying
possible fluctuations in customer demand, inventory, and resources
(i.e., material, labor, and equipment). The digital twin uses the
knowledge from data modeling and analysis to enable demand-driven,
on-time delivery, resource optimization, cycle-time reduction, and
inventory-cost reduction.

Virtual Commissioning Digital Twin –
Commissioning a manufacturing system can be very expensive and
time-consuming. As an alternative, virtual commissioning can be used to
identify and resolve issues before investment and avoid costly
adjustments during or after installation of manufacturing equipment. A
virtual commissioning digital twin is a dynamic, virtual representation
of its corresponding physical element (e.g., a machine, a cell, a line
or a system) that is used to substitute its physical element for the
purpose of commissioning. It needs to be modeled at the level of sensors
and actuators. For example, the Programmable Logic Controller (PLC)
logic and rules need to be represented within a machine digital twin.
Depending on the purpose, there could result many different virtual
commissioning digital twins, for example, a virtual commissioning of an
existing production system (i.e., the manufacturing equipment was
installed but needs adjustment) or a virtual commissioning of a newly
designed production system (i.e., manufacturing equipment is not in
place or not even purchased).⁹

A Universe of Interested Parties

One major factor contributing to the popularity of digital twins is
their broad and diverse client base. Dr. Martin Hardwick, president of
STEP Tools, has identified the beneficiaries of digital twin technology
by occupation. The following represents a partial list:

• Owners – Want to know the real time status of their operations.
• Operators – Want to prevent mistakes.
• Engineers – Want to eliminate non-value-added tasks.
• Maintenance Workers – Want insight into why equipment is failing.
• Subcontractors – Want information to prepare better bids.
• Equipment Suppliers – Want information to enable easier
  integration.
• IT Developers – Want to ensure security, especially reliable access
  control.
• Regulators – Want to measure compliance.
• Software Vendors – Want to expedite deployment of their solutions.
• Standards Development Organizations – Want to promote their
  standards.¹⁰

Future of Digital Twins

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“Digital twins can
profoundly enhance an enterprise’s ability to make proactive,
data-driven decisions, increasing efficiency and avoiding potential
issues.”

– Deloitte¹¹

Cognitive Twins

As might be expected, analysts Matthew Mikell and Jen Clark anticipate
that artificial intelligence (AI) will greatly influence the evolution
of digital twins. “Technologies and techniques such as Natural Language
Processing (NLP), machine learning, object/visual recognition, acoustic
analytics, and signal processing are just a few of [the] features
augmenting traditional engineering skills. Cognitive digital twins can
take us beyond human intuition to design and refine future machines. No
more ‘one-size-fits-all’ model, but instead, machines are individually
customized. That’s because [the] cognitive digital twin is not just
about what we are building, but for whom.”¹²

Predictive Twins

In addition to the digital twin, a new form of twinning is emerging:
the predictive twin. Citing the example of an Oracle digital-twin
tool that offers both digital and predictive options, analyst Deepak
Puri says the predictive version can “[model] the future state and
behavior of [a] device. This is based on historical data from other
devices, which can simulate breakdowns and other situations that need
attention.”¹³

IoT-Enabled Twins

In the future, the principal enabling technology for digital twins will
be IoT and, in particular, IIoT sensors. As IoT sensors are reduced in
size and improved in function, digital twin scenarios can incorporate
smaller and less complex objects, thus generating more digital
substance.

As analysts Keith Shaw and Josh Fruhlinger observe, “Digital twins can
be used to predict different outcomes based on variable data. This is
similar to the run-the-simulation scenario often seen in science-fiction
films, where a possible scenario is proven within the digital
environment. With additional software and data analytics, digital twins
can often optimize an IoT deployment for maximum efficiency, as well as
help designers figure out where things should go or how they operate
before they are physically deployed.” In short, “the more that a digital
twin can duplicate the physical object, the more likely that
efficiencies and other benefits can be found.”¹⁴

Human Twinning

It may sound scary at first, certainly creepy, but the ability to twin an
actual person is not far off. As the BBC reports:

Mr. Enderle thinks that ownership of such
digital twins will become one of the defining questions of the impending
metaverse era.¹⁵

Meta Twins

Digital twins will be vital tools in the development of various
versions of the “metaverse”. For example, the metaverse, as manifested
through Microsoft’s Azure Digital Twins technology, is proving an
invaluable instrument for business process reengineering, improving
business productivity, reducing errors, lowering costs, and enhancing
customer experiences. Azure Digital Twins is an Internet of Things (IoT)
platform that enables enterprises to create a digital representation of
real-world things, places, people, and business processes, helping
optimize operations. Utilizing sensors and IoT communications, the digital
view can be synced up with the physical view and vice versa.
“Anheuser-Busch InBev, [for example], used Azure Digital Twins to create a
complete digital model of their breweries and supply chain that syncs up
in real-time with the physical environment.”¹⁶

According to Orange, a leading communications network operator, “[these
intrinsic properties make digital twins one of the fundamental building
blocks of the metaverse. While the metaverse may be able to bring us
virtual worlds and experiences beyond what we can imagine, it will also
have many uses in creating exact replications of reality.”¹⁷

As analyst Shubham Sharma explains, other prominent enterprise use cases
include:

• Customer Support – “Digital twins of customer service agents
  could assist customers in an immersive, shared digital space, helping
  them assemble, repair, or exchange their products.”
• Sales and Marketing – “Various automakers, including Nissan
  and Mercedes, have … created virtual showrooms to give prospective
  buyers a good look at their vehicles inside out and drive sales.
• Scenario Planning – “Since there are no physical constraints
  in the virtual world, enterprises could … use the metaverse as a way
  to ensure effective scenario planning and problem management.”¹⁸

Ultimate Vision

As we spy the future, “The ultimate vision for the digital twin is to
create, test and build our equipment in a virtual environment,” says
John Vickers, manager of NASA’s National Center for Advanced
Manufacturing. “Only when we get it to where it performs to our
requirements do we physically manufacture it. We then want that physical
build to tie back to its digital twin through sensors so that the
digital twin contains all the information that we could have by
inspecting the physical build.”¹⁹

Before this vision can be realized, however, enterprise planners must
prepare the enterprise workplace and workforce. Like other recent
innovations, including cloud computing and managed services, digital
twins are disruptive.

As analyst Kasey Panetta warns, “Digital twins function as proxies for
the combination of skilled individuals (e.g., technicians) and
traditional monitoring devices and controls (e.g., pressure gauges).
Their proliferation will require a cultural change, as those who
understand the maintenance of real-world things collaborate with data
scientists and IT professionals.”²⁰

Finally, as Microsoft’s Simon Floyd and Mike Nicholas remind us,
“Designers and engineers live for the big breakthroughs, but most
innovation cycles are about incremental improvement.

“You can use digital twin virtualizations to:

• “Develop insights about how existing equipment, processes, or
  products perform over time;
• “Use the information to influence and validate new prototypes; and
• “Bring better products to market faster, at less cost.

“That makes the real breakthroughs more achievable, more
cost-effective, and better aligned with the full product lifecycle.”²¹

References

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¹ Bernard Marr. “What Is Digital Twin Technology – And Why
Is It So Important?” Forbes. March 6, 2017.

² “Digital Twin Market: Global Industry Trends, Share,
Size, Growth, Opportunity and Forecast 2022-2027.” Research and Markets.
March 2022.

³ Kasey Panetta. “Gartner’s Top 10 Strategic Technology
Trends for 2017.” Gartner. October 18, 2016.

⁴ Gitanjali Maria. “What Is Digital Twin Technology, and How
Do You Ready Your Business for It?” Software Advice, Inc. May 18, 2020.

⁵ Bernard Marr. “What Is Digital Twin Technology – And Why
Is It So Important?” Forbes. March 6, 2017.

⁶ Lynne Slowey. “What Is Digital Twin?” IBM. March 16, 2017.

⁷ Bernard Marr. “What Is Digital Twin Technology – And Why
Is It So Important?” Forbes. March 6, 2017.

⁸ “15 Digital Twin Applications and Use Cases by Industry in
2022.” Jama Software. May 31, 2022.

⁹ Guodong Shao. “NIST Advanced Manufacturing Series 400-2:
Use Case Scenarios for Digital Twin Implementation Based on ISO 23247.”
US National Institute of Standards and Technology. May 2021:12-25.

¹⁰ Dr. Martin Hardwick. “Assessment of Digital Twin
Manufacturing Frameworks.” US National Institute of Standards and
Technology. 2020.

¹¹ Charlie Osborne. “The Rise of the Digital Twin: Why the
Enterprise Needs to Take Notice.” CBS Interactive. May 3, 2018.

¹² Matthew Mikell and Jen Clark. “Cheat Sheet: What Is
Digital Twin?” IBM. January 4, 2018.

¹³ Keith Shaw and Josh Fruhlinger. “What Is a Digital
Twin? (and How It’s Changing IoT, AI and More).” IDG Communications.
January 31, 2019.

¹⁴ Ibid.

¹⁵ Jane Wakefield. “Why You May Have a Thinking Digital Twin
within a Decade.” BBC. June 13, 2022.

¹⁶ Bernard Marr. “The Enterprise Metaverse: What It Means
for Businesses.” Bernard Marr. October 22, 2021.

¹⁷ “Journey Through the Metaverse: Digital Twins Are
Synchronizing the Physical and Virtual.” Orange. December 3, 2021.

¹⁸ Shubham Sharma. “7 Ways the Metaverse Will Change the
Enterprise.” VentureBeat. January 26, 2022.

¹⁹ Bernard Marr. “What Is Digital Twin Technology – and Why
Is It So Important?” Forbes. March 6, 2017.

²⁰ Kasey Panetta. “Gartner’s Top 10 Strategic Technology
Trends for 2017.” Gartner. October 18, 2016.

²¹ Simon Floyd and Mike Nicholas. “Optimize and Innovate:
How Digital Twins Transform Manufacturing.” Microsoft. April 21, 2017.

Web Links

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• GE: http://www.ge.com/
• IBM: http://www.ibm.com/
• Microsoft: http://www.microsoft.com/
• US National Institute of Standards and Technology: http://www.nist.gov/

About the Author

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James G. Barr is a leading business continuity analyst
and business writer with more than 30 years’ IT experience. A member of
“Who’s Who in Finance and Industry,” Mr. Barr has designed, developed,
and deployed business continuity plans for a number of Fortune 500
firms. He is the author of several books, including How to Succeed
in Business BY Really Trying, a member of Faulkner’s Advisory
Panel, and a senior editor for Faulkner’s Security Management
Practices. Mr. Barr can be reached via e-mail at jgbarr@faulkner.com.

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