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Digital Twin

By: Gabby Dumonceaux | Reviewed by Margaret RouseCheckmark | Last updated: August 31, 2022

What Does Digital Twin Mean?

A digital twin is a virtual representation of an entity or system that exists in the physical world.

Digital twins can be either static or dynamic. Static twins, which are also referred to as simulations, represent an entity or system at a specific point in time. Dynamic twins are linked to the physical entity or system they represent in order to accurately depict the state of the entity or system in real or near-real time.

Popular uses for digital twins include:

  • Forecasting the health of an entity or system under specific conditions.
  • Training staff how to use/manage a physical entity or system.
  • Capturing requirements for a new entity or sytem.
  • Predicting how a change will affect a real-world entity or system.
  • Comparing two different lifecycle plans for an entity or system.
  • Understanding an entity or system's dependencies prior to building it in the real world.
  • Testing dangerous scenarios without involving people.
  • Assessing risk without causing a serious impact.
  • Simulaneously running simulations for different "what if" scenarios.

Digital twins are often associated with manufacturing, the military and information technology. The label "digital twin" was coined at NASA, where the term was first used to describe a product lifecycle management (PLM) strategy to.

Today, digital twins play an important role in many industries -- especially those industries that rely on multiplex computing systems or use complex physical entities that are both valuable and unique.

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Techopedia Explains Digital Twin

Digital twins help engineers in many many industries to understand the current state of something and make predictions about its future. The desire to eliminate waste and improve ROI often cited driver this type of initiative.

Digital Twins and Hyperautomation

When digital twins are used to model how various workflows can be automated, the concept is often referred to as hyperautomation.

The goal of hyperautomation is to automate workflows from beginning to end. Digital twins can help with this because they provide companies in any industry with a way to manage change -- and test high-risk ideas -- without impacting the physical world.

When a dynamic digital twin uses machine learning to make decisions autonomously, it may also be referred to as a cognitive digital twin.

Digital Twin vs. Simulation

Although the terms digital twin and simulation are often used as synonyms -- they are actually two different things.

Simulations can only use historical data to predict what impact a change will have. In contrast, a digital twin is able to use real-time data to make predictions.

Industries Using Digital Twins

Cloud computing and Intrastructure-as-a-Service (IaaS) delivery models have lowered the cost of running a digital twin. Because executing the concept has become much more affordable in recent years, the use of digital twins is growing steadily.

Digital twins play an important role in research and development (R&D), system integration, change management, customer experience management, and enterprise risk management.

Industries using digital twins to mirror complex systems and gain better visibility into system dependencies include:

  • Aerospace
  • Architecture
  • Construction
  • Design
  • Engineering
  • Finance
  • Healthcare
  • Information Technology
  • Manufacturing
  • Retail
  • Supply Chain


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Risk ManagementIT Business AlignmentArtificial Intelligence

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