8 Myths About Digital Twins Exposed—Here’s the Reality
Joe Walsh posted on July 30, 2020 |
Excitement, hype and confusion about an emerging technology. So, what else is new?
(Picture courtesy of Plataine.)
(Picture courtesy of Plataine.)

There has been an increasing interest in digital twins for multiple purposes over the last few years, which has been accompanied by excitement, hype and confusion. Several software vendors have adopted digital twins as a critical part of their strategies and positioning for various reasons. Multiple organizations are looking at the technology as an integral part of their digital transformation efforts.

This interest and excitement have also led to an overabundance of hype from vendors and has resulted in confusion in the marketplace regarding digital twins. The confusion comes from an unclear definition of what a digital twin is. The lack of clarity is not due to a lack of definitions. Instead, the it is due to an overabundance of conflicting and vague definitions as each interested party publishes their definition of the technology based on their approach and implementation of digital twins.

The Reality: There’s All Kinds of Digital Twins

The simple truth is that there are multiple forms of digital twins for a wide variety of purposes. Each form of a digital twin has specific characteristics to meet its intended goals. However, there are two fundamental and common characteristics of digital twins across all of the different forms and purposes.

Rules for a digital twin:

  1. A digital twin must have a corresponding physical twin.
  2. There is bidirectional information flow between the digital and physical twin, allowing each to exploit the other.

The Myths

There are multiple myths about digital twins that need to be addressed to enable a common understanding of the technology that is essential for broad usage and benefit. This section will outline some of the common myths about digital twins.

Myth 1: There Is a Single Digital Twin

There is no single digital twin for a physical twin with all of the virtual information associated with it. Any physical twin may have multiple associated digital twins for different purposes. Each digital twin can provide a specific capability or functionality. Different digital twins are developed for different purposes, with each digital twin providing the functionality to meet that particular purpose. Lacking a digital twin that is a mirror image of the physical twin, perhaps the term digital cousin would be more accurate.

Myth 2: All Digital Models Are Digital Twins

A digital twin must have a physical twin. This myth is just marketing hype to make an unrelated product offering fit in the digital twin envelope. Common sense and the common characteristics outlined above make it very clear that in order for there to be twins, there must be two entities.

Myth 3: A Digital Twin Needs to Cover the Entire LifeCycle of the Physical Twin

A digital twin does not need to cover the entire lifecycle of its physical counterpart. Different digital twins are each developed for different purposes, with a digital twin covering an appropriate portion of the physical twin lifecycle to align with the purpose of that particular digital twin.

Myth 4: A Digital Twin Needs to Be Physics Based

While a specific capability or functionality of a twin may need to be physics based, not every twin will have the same need. For example, one digital twin may give only a visual similarity to its physical counterpart, whereas an engineering simulation digital twin must be physics based.

Myth 5: A Digital Twin Needs to Leverage the Internet of Things (IoT)

While both the IoT and digital twins are currently emerging technologies, they are not always together. From the Reality of Digital Twins, rule 2 (above), a digital twin must exploit information to/from its physical twin. However, the means to do so can vary based on the form and purpose of the digital twin. IoT will significantly expand the possible use and forms of digital twins. Still, digital twins can and do exist that do not leverage IoT. The method used to obtain or exploit the information to and from the physical twin may be used as a basis to describe specific forms of digital twins but not as a requirement to be a digital twin.

Myth 6: A Digital Twin Needs to Continually Communicate with the Physical Twin

Different digital twins are developed for different purposes, with each digital twin providing communication to/from the physical twin to meet that purpose as frequently as needed. Communication can be intermittent or periodic, rather than streaming.

Myth 7: A Physical Twin Refers to a Single Physical Entity/Asset

A physical twin can be any meaningful aggregation of physical assets or processes (e.g., a fleet of airplanes, a model year for a specific car, a population of a shared demographic characteristic, etc.).

Myth 8: Digital Twins Are Used Only by Engineering

Digital twins are useful for engineers but are not the sole domain of engineers. Any discipline can create digital twins to mirror different phenomena. For example, a financial digital twin that models a company’s business performance, a logistical digital twin that models a supply line, a medical digital twin that simulates vaccine reactions, and so on.

A Usable Standard Definition of Digital Twins

Perhaps it’s time to formulate a definition of digital twins that considers but is independent of its various implementations. The overall definition of digital twins should be neutral to any particular implementation and should cover all forms of digital twins. Based on the two common characteristics of a digital twin outlined earlier, two potential standard definitions for a digital twin are presented here.

CIMdata definition:

“A digital twin is a virtual representation of a physical asset or collection of physical assets (physical twin) that exploits information flow to/from the associated physical asset(s).”

NAFEMS SMSWG (Systems Modeling and Simulation Working Group) definition:

“The digital twin is a digital surrogate that is a description of a physical asset, such as products, processes, systems, people and devices, that can be used for various purposes. The digital twin makes use of data and information from the real-world asset and provides feedback to this real-world asset.”

With a clear definition of a digital twin, it is now possible to explore the multiple forms of digital twins and their associated definitions. There are multiple forms of digital twins for a wide variety of purposes. Each form of a digital twin has specific characteristics to meet its intended goals and should have a more detailed definition outlining the specific capability, functionality or implementation associated with that form of digital twin. The ASSESS Initiative has established a key theme and working group around Engineering Simulation Digital Twins and has provided the following definition of an Engineering Simulation Digital Twin:

“An engineering simulation digital twin is a physics-based virtual representation of a physical twin (physical asset or a meaningful aggregation of physical assets) that exploits information flow to/from the associated physical twin.”


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