The digital twin explained: a look at your most frequently asked questions [FAQs]

The word ‘twin’ brings to mind the concept of similarity, of a replica. It makes you think about two things or two people. In the same way,  a ‘digital twin’ brings to mind a copy, or a second version of something, with a view of the copy being virtual.

In this article, we look at what a digital twin is, and respond to your most Frequently Asked Questions – what a digital twin is, what it is used for, how it works, and current use cases.

What is a digital twin?

A digital twin can be defined as a virtual representation of an existing or potential entity, person, place, device, process, or system during its lifecycle. It is important to note that the virtual replica must be connected to its physical counterpart, where the physical counterpart exists, in order to collect real-time data and mimic changes that occur in the physical counterpart.

Who invented the digital twin? When?

The idea or concept of the digital twin was created in 2002 by Dr. Michael Grieves. The world first heard of it when he made a presentation at the University of Michigan that was aimed at the creation of a Product Lifecycle Management center.

Initially, the digital twin technology was a preserve of companies or organizations with the infrastructure and financial backing to collect, store and process the massive amounts of data that the technology generated. With technological advancements like IoT, more and more companies are now able to use digital twin technology.

During the Gartner 2017 Symposium/ITxpo, the digital twin was the number 4 trend among the top 10 strategic technology trends for 2018 (image below). This led to a piqued interest in the technology.

Top strategic technology trends
Top strategic technology trends

What are digital twins used for?

Digital twins can be used in several ways. These include:

  • creating product simulations before building the actual product
  • studying the performance of physical entities in order to make the necessary improvements and data-informed decisions
  • collecting and analyzing data from existing physical assets in order to make predictions based on ‘what-if’ scenarios

What is a digital twin of an organization [DTO]?

When you create a digital twin of your organization, then you have created a DTO.  Gartner defines a DTO as a dynamic software model that relies on data, whose main functions include understanding how an organization implements its business model, responds to changes and utilizes its resources in order to deliver customer value.

The fact that we can have DTOs is an indicator of the fact that complex digital twins can be developed.

How does a digital twin work?

The creation of the digital twin begins with a study of the existing physical counterpart, its physical model or its prototype. The underlying mathematics and physics are then studied with an aim to digitally replicate the physical entity. The digital replica is then built and equipped to receive data from its physical twin.

It is important to note that sometimes, where the physical entity does not exist, it is still possible to build a virtual model which is a simulation of the physical item that will be later created.

Once the virtual twin is ready, its physical counterpart is then equipped with sensors to allow for data transmission between the two versions. The data is transmitted over the cloud.

Depending on the complexity of the models, machine learning algorithms may be used to help with data interpretation and predictions.

The collected data is then replicated in the virtual twin.

What are the types of digital twins?

As we have mentioned, digital twins differ in terms of complexity. They also differ in terms of simulation levels. Let’s explore the different digital twin types:

GE defines the following types of digital twins, depending on their complexity and the level of abstraction they represent (image below)

  • Component
  • Asset
  • System
  • Process
Digital Twin Types


As you can tell from their names, a component digital twin (for example a bearing) will represent a component of an asset like a pump, while a system digital twin will be a representation of a process like a production line which is part of a bigger system, for the entire manufacturing process.

Digital twin use cases

Digital avatars can be used in various industries. They can be used in healthcare for example, to help with patient flow to avoid bottlenecks, or even in consumer insights to track how users interact with a product.

Here are practical use cases where digital avatars have successfully been used:

NASA – use digital twins to research on the future of Air Force vehicles which need to carry heavier loads but have lighter mass.

Siemens – has a company called Digital Industries (DI) which has helped to design and manufacture an electric car dubbed ‘solo’.

GE – used digital twin technology to build digital turbines which collect data from their physical twins, which helps to predict things like the impact of strong winds on physical wind turbines.

In conclusion

As we have seen, digital twin technology makes it possible to create digital replicas of entities. This can come in handy even for your business, as you can embed sensors into your physical products and study how your customers interact with them, thanks to technologies like IoT.

You can start small, with a digital avatar of one of your components, before going full throttle. You can also look at aspects of your business that you can create a digital twin of. This will allow you to test for conditions even before they happen, or build prototypes at a much lesser cost.

You can also create a digital twin of your customer – a digital profile that tracks your target customer’s digital footprint. Every time your customer takes an action like purchasing, writing a review, adding to cart, then the twin is updated, giving you valuable insights.

Have you begun your digital twin journey? Tell us about it.