16 November 2023
What Is A Digital Twin, And How Does It Work?
Digital twins are a powerful tool for gaining deep knowledge of products or processes without interfering with them directly.
NASA began using the concept of “digital twins” in the 1960s as part of the Apollo space programme. The agency used them to simulate the characteristics of in-flight orbiting and lunar vehicles they couldn’t observe directly.
The modern digital version arrived in 2002 as aerospace and other high-value industries wanted to study objects without testing them directly. Companies saw the value of creating digital equivalents of physical processes or products and testing them in various ways.
This post describes what a digital twin is and how it works. Then, we discuss the purpose of the concept in various industries and how engineers use it.
The Digital Twin Concept
A digital twin is a virtual representation of a physical process, product, or entity. The goal is to use the digital version to study the item in question more thoroughly or comprehensively, often at a lower cost than trying to investigate it directly.
How Do Digital Twins Work?
Digital twins gather data about the object of interest through heat, temperature, pressure, and gyroscopic sensors. Then, computers feed this information into software, letting engineers play with various parameters to see how the digital copy will respond. The results suggest how changing the parameters of the virtual object might affect the original physical instantiation.
For instance, suppose a company wants to evaluate a wind turbine’s ability to withstand stormy weather but can’t recreate it in a laboratory. Digital twins could function as a substitute by collecting data from the wind turbine’s sensors and feeding this into a simulation that projects likely outcomes based on variable wind speeds and temperature fluctuations. This method might let engineers estimate the risk of failure or catastrophic damage to the turbine’s engine or blades.
Digital twinning is not the same as simulation. Simulations typically study a single variable, while a digital twin attempts to recreate the physical characteristics of the study object, allowing multiple configurations.
Simulations also lack the real-time data digital twins use. Engineers can get a better sense of an object’s physical situation in relation to parameters using the latter without having to make as many conditional assumptions.
Interestingly, digital twins do not necessarily need to depict their real-world counterparts graphically. Computers can store information in various formats, including spreadsheets, sets of equations, and datasets. What counts is the conclusions that the digital twin lets engineers draw. Data outputs provide new information about the performance of a process or product outside of current operating parameters. Models must enable deeper investigation and querying of the data.
This concept can be confusing, so let’s boil it down to the essentials. Digital twin technology:
- Synchronises the physical entity with a digital representation using sensor data
- Allows engineers to adjust parameters affecting the digital twin to assess performance
- Allows high-fidelity, precision study of the digital twin using real-time data from the physical object
You can also think of digital twins in terms of a three-part model:
- The physical object
- The communication layer between the physical object and the digital twin
- The digital twin
The data layer continually communicates between the two entities, ensuring the digital twin accurately reflects reality. This approach means the computerised representation of products and processes can vary significantly, even if the manufacturer specifications are identical.
What Types Of Digital Twins Are There?
Digital twins can model real-world systems of increasing complexity.
The most basic is “component twins.” Engineers might pair a single washer or O-ring with a digital twin and feed data via a software layer to predict how it might behave or when it needs maintenance.
“Asset twins” are the next step in the hierarchy. These represent the status of physical systems with two or more components. Engineers can use the ensemble of data to generate more profound insights into the systems’ overall functionality.
“System twins” are the next step up. These enable engineers to model how multiple assets come together and interact. Zooming out to this level of magnification can help enhance efficiencies and ensure parts perform optimally together.
“Process twins” are fully zoomed-out digital representations of complex, multi-asset, multi-system operations. For example, organisations will frequently use them to measure the performance of their whole production facility.
How Industries Use Digital Twins
Industries use digital twins in multiple settings for deeper insights into their operational effectiveness. Here are some areas firms use them in today.
Retailers use digital twins to model their supply chains and track inventory. Companies that understand how they work can avoid over- or under-stocking.
Retailers also use digital twins in-store layout optimisation. Digital representations of shop floors can predict optimal product arrangements based on footfall and floor traffic.
Aerospace firms use digital twins to represent aircraft fuselages, engines, and other components. Sensors gather copious data and send it to software to estimate likely maintenance intervals, reducing downtime.
The aerospace industry may also use digital twins for flight simulations before engaging in production runs of an aircraft model. Engineers can use this approach to tease out superior aerodynamics and fuel efficiency.
Digital twins are also helpful in healthcare. The software can take a patient’s medical history, genetic information and real-time biometrics and use them to create a digital twin. Medical personnel can then experiment on the digital version to assess likely outcomes before making recommendations to the human patient.
Digital twins help manufacturers monitor their machinery’s condition. Numerous sensors collect data, letting them build a digital representation of their productive assets. The replica can then help teams estimate when breakdowns might occur and repairs may become necessary.
The value of digital twins is tremendous, similar to our online chat for website owners love. Representing complex physical objects in physical formats enables engineers to play and tinker with systems without harming costly physical capital while still deriving insights.
Interestingly, agents can do something similar with customers. Taking their information using live online chat software, they can evaluate the likely impact of certain lines of conversation, products, or services on sales or conversions.