Introduction to Digital Twins: Optimizing the Real World through the Virtual World

If you asked me, I’d say that Iron Man is the most realistic character out of all the superheroes in the MCU. I’m sure there are other heroes who have no gamma rays, radioactive spiders or super-soldier serums but, for the purpose of this article let’s stick with Iron Man.

When Stark creates the first Iron Man Nano suit, he goes through a series of processes such as designing the suit, making a prototype, trying out the prototype, checking its size, testing its performance before finally coming up with the final product. The technology that allows for all of that to happen efficiently is called a digital twin.

We are in an era where the Internet of Things is becoming more prevalent. With the new 5G network, cars are becoming more connected and objects with sensors can communicate with people and other devices as they become smarter by the minute.

Digital twins have gone beyond manufacturing and entered the world of IoT, AI and data analytics. As objects become more complex through connection, data scientists and IT professionals have the ability to optimize these objects for peak efficiency and create what-if scenarios. From healthcare to manufacturing or retail, the implementation of digital twins is spreading.

“ 50 percent of large manufacturers will have at least one digital twin initiative launched by 2020, and the number of organizations using digital twins will triple by 2022. — Gartner Survey ”

What is a Digital Twin?

“A digital twin is the virtual representation of a physical object or system across its life-cycle. It uses real-time data and other sources to enable learning, reasoning, and dynamically recalibrating for improved decision making.”

Digital Twins are seen as a bridge between the real world and the virtual world. It uses sensors to collect data on a physical object to create a virtual replica. The technology behind digital twins has expanded to include large items such as buildings, factories, cities and even people or processes. If the term ‘digital twins’ is still confusing, here is example of how digital twins work from Challenge Advisory.

Digital Twin for Road Infrastructure: In order to improve the transportation and travel systems in New York City, the government decided to create an initiative and build a digital replica of the city itself. By building out an entire city on a digital platform, engineers are now able to develop digital road systems underground and accurately predict how this new transportation system will incorporate itself with normal roads of New York City. Finally, by having data on the average deterioration rate of a road in one of the busiest streets of the city, they are able to make safe predictions on how often the new underground roads will need to be replaced in order to ensure the security of the new road system.

Before diving deeper into Digital Twins, let’s me clear up two common misconceptions about Digital Twins.

  1. Digital Twins is a concept, not a single product or a piece of technology. In a paper published by Abdulmotaleb El Saddik, a distinguished University Professor, he explores the different emerging technologies that make up Digital Twins. These technologies include, 3D simulation, IOT, 4G/5G, big data, blockchain, Edge, cloud computing, AR/VR and artificial intelligence. All of these come together to make the concept a reality and far more useful and cost-effective.
  2. Digital twins shouldn’t be confused with digitization. Olesia Martynova, an IoT practice leader explains that Digital Twins don’t substitute the physical object with a digital one to make it more accessible, efficient, or secure. Instead, it’s a precise replica of the physical object and a means of testing and monitoring it without needing access to the physical object.

How did the concept of Digital Twin come to be about?

The concept of Digital Twins is nothing new. The idea first appeared in a 1991 book called Mirror Worlds by David Gelernter. Later on, Michael Grieves applied this concept into manufacturing. In 2002, he formally introduced the concept of the digital twin at a Society of Manufacturing Engineers conference.

Grieves explained the idle product lifecycle management and established the connection between real objects and the virtual images. He explained that each system consists of real and virtual components which contain all the information about the real objects. He called this concept the information-mirroring model which was applied in NASA’s Apollo 13 project and later coined the name ‘Digital Twin’

However, it wasn’t after IoT devices became widespread that we were able to discover the full potential of digital twins. In 2017, Gartner named digital twins as one of its top 10 strategic technology trends for 2017 saying that within three to five years, “billions of things will be represented by digital twins, a dynamic software model of a physical thing or system”. In 2018, Gartner named digital twins as a top trend, saying that “with an estimated 21 billion connected sensors and endpoints by 2020, digital twins will exist for billions of things in the near future.”

Where are Digital Twins used?

Digital twins are and can be used in a wide variety of industries for a range of applications and purposes. Here are some of the current applications but there are many more use cases for Digital Twins.

Automotive: The Automobile Industry continues to adopt the latest technologies and experiment with new ideas. Digital twins can assist with test drives and sensor operations to ensure safety. This can help to reduce the production cost. Some reputable automobile companies have already successfully adopted digital twin technology.

  • Tesla Motor company that highly invested in digital technology to provide reliability for its car owners. Tesla creates a digital twin for every car they sell and update software integrating with sensors. This process empowers adequate resource allocation and reliable user experience.

Retail: Appealing to a customer experience is key in the retail sector. Digital twins can play a key role in augmenting the retail customer experience by creating virtual twins for customers and modeling fashions for them on it. This can truly enhance the customer experience. Digital Twins also helps in better instore planning, security implementation and energy management in an optimized manner.

Healthcare: So far, the medical sector has benefitted from digital twin in areas such as organ donation, surgery training and de-risking of procedures. In addition, a digital twin of a human body can diagnose many hidden details of a body’s organ. As a result, many research companies have already started using digital twins to virtually create human organs and test the effects of drugs/treatments. For instance:

  • Digital twin heart developed by Siemens Healthiness uses a series of algorithms, MR images, and ECG measurements to facilitate visual responses to treatments, before undergoing the physical process.

Smart Cities: Urban planning and development are an enormous budget scheme. Poor city deign can lead to more money being spent later on to redo it. Digital twins can help cities become more economically, environmentally and socially sustainable. With integrated IoT and big data, digital twins can facilitate decisions and create solutions to complex challenges by cities. In addition, it allows designers to test out ideas before implementing it.

  • The city-state of Singapore, collaborating with digital twin technology plus three-dimensional semantic models of the city, a virtual city designed by the National Research Foundation (NRF).

How Digital Twins could be used to Analyze/Monitor a Physical Product

According to Sky Matthews, CTO of IBM Watson IoT, there are three key factors that have advanced the technology of digital twins:

  • Velocity — The rise of IoT devices have made it relatively easier to collect massive volumes of data and transfer it to a digital twin in almost real time.
  • Resolution — Digital information helps us get a close look at the finest details of physical assets making the twin almost identical to the physical object.
  • Learning — Machine learning algorithms analyze the gathered data and make predictions, refining the digital twin based on the gathered information and calibrating the general model and its details.

These factors have changed how the Digital Twin is used. Here is a video from 2017 of how a digital twin works and is used. Imagine how much faster and precise it is now with 5G internet and more innovation in all the areas of technology.

The video above only showed a little glimpse of twin technology in the industrial world. Something to take note of is the 3 step process on how a digital twin could be used.

See the physical object — The digital twin gathers data of situation to give a warning or prediction.

The data gathered through sensors allows a digital twin to act like the real object and create a virtual representation. In this case, it’s monitoring the actual product and warning us of a future problem.

Think — Runs Simulations to give different options at what it can do and reasons through the options

Instead of having us make assumptions, the twin could simulate a scenario to see how the product will perform. We can manipulate it, monitor various parts and pieces, test new approaches, predict breakdowns, and more. Instead of making assumptions based on general expectations, companies can now actually see, feel the process, and influence it.

Do — The Digital Twin can inform us or execute what needs to be done to solve/prevent the problem

Depending on the options given (manual vs. digital), if it is a manual, the twin can inform us of the necessary product sizes, computational digits that need to be manually inserted etc. On the other hand, if it’s a digital fix, the twin could automatically adjust through online applications.

How Digital Twins could be used to Create a Product

Now I’ll walk through the use of a Digital Twin to build a product from scratch, using an example of building a car from Siemens. There are three types of digital twins that can contribute to a product of high performance and efficiency; Digital Product, Production and Performance Twins.

Product Twins: Using digital twins for efficient design of new products

A ‘product digital twin’ provides a virtual-physical connection that lets you analyze how a product performs under various conditions and make adjustments in the virtual world to ensure that the next physical product will perform exactly as planned in the field.

Designing Car in Detail with NX CAD with Siemens

Designing a product is one of the most complex and expensive phases of the product lifecycle. Research and Development (R&D) teams have used computer-aided design (CAD) systems to develop products. However there are still many limitations and constraints to our current 3D simulations. Testing prototypes costs a lot of money if a company finds an undesired/unexpected behavior in their product and have to go back to the drawing board to make changes.

Simulating car to understand it’s external and internal behavior with Siemens

With digital twins, multiple environments can be spun off easily and inexpensively to simulate scenarios. We can design models collaboratively and simulate various test conditions. Organisations don’t have to worry about high costs and through testing, the quality of the end-product can improve.


  • Eliminates the need for multiple prototypes
  • Reduces total development time
  • Improves quality of the final manufactured product
  • Enables faster iterations in response to customer feedback.

Production Twins: Using digital twins in manufacturing & production planning

A ‘production digital twin’ can help validate how well a manufacturing process will work before anything actually goes into production. By simulating the process using a digital twin and analyzing why things are happening using the digital thread, companies can create an efficient production methodology.

Production Planning with Siemens

Running smooth operations are critical for any business. With many moving parts, critical information like clashes and conflict among the parts cannot be captured in the digital world. When there are many variables that contribute to a production process, it’s literally impossible for a human to control.

Planning an entire production line and selecting the production equipment like robots and conveyor belts.
Planning an entire production line and selecting the production equipment like robots and conveyor belts.
Planning an entire production line and selecting the production equipment like robots and conveyor belts

Digital Twins not only help to provide insights into parts and components but can identify and show large interconnections of the production environment. We can communicate with the twin and ask what-if questions and simulate their impact, without affecting the real production. Any changes made in the real production, gets reflected in the twin.


  • The production can be optimized even further by creating product digital twins of all the manufacturing equipment.
  • Using the data from the product and production digital twins, businesses can prevent costly downtime to equipment
  • predict when preventative maintenance will be necessary.
  • Enables manufacturing operations that are faster, more efficient, and more reliable.

Performance Twins: Using digital twins to capture, analyze, and act on operational data

Smart products and smart plants generate massive amounts of data regarding their utilization and effectiveness. The performance digital twin captures this data from products and plants in operation and analyzes it to provide actionable insight for informed decision making.

Many operations struggle with poor knowledge management. Figuring what occurred to cause unnecessary downtimes, failures or damages is an uphill task.

Analyzing the Product and Production to see if it can be proved upon even more with Siemens

In Digital Twins, the physical properties and data from the sensors are combined with sophisticated prediction algorithms. This help to move enterprises from “what has happened” to predicting “what is likely to happen.” Digital Twins can also serve as a knowledge management hub, storing historical states and performance of the product/production, predicted future state and design-information.

By leveraging performance digital twins, companies can:

  • Create new business opportunities
  • Gain insight to improve virtual models
  • Capture, aggregate, and analyze operational data
  • Improve product and production system efficiency


Digital twins are already helping organizations stay ahead of digital disruption by understanding the changing customer preferences, customizations and experiences. Imagine what would happen if we were the product. We could simulate treatments, predict illnesses ahead of time and understand our bodies at a whole new level. Maybe we could all have our own personalized Nano suit. After all, there’s really no limit to how digital twins can impact our world.

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17y/o innovator interested in impacting the world through exponential technologies. Always learning, Always growing | IoT & AR/VR Enthusiast

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