#30 - What is Digital Twin? - 1

A digital twin is a digital representation of a physical object, process, or service. A digital twin can be a digital replica of an object in the physical world, such as a jet engine or wind farm, or even larger items such as buildings or even whole cities.

As well as physical assets, the digital twin technology can be used to replicate processes in order to collect data to predict how they will perform.

A digital twin is, in essence, a computer program that uses real-world data to create simulations that can predict how a product or process will perform. These programs can integrate the internet of things (Industry 4.0), artificial intelligence, and software analytics to enhance the output

With the advancement of machine learning and factors such as big data, these virtual models have become a staple in modern engineering to drive innovation and improve performance.

In short, creating Digital Twin can allow the enhancement of strategic technology trends, prevent costly failures in physical objects, and also, by using advanced analytical, monitoring, and predictive capabilities, test processes, and services.

How Does Digital Twin Technology Work?

The life of a digital twin begins with experts in applied mathematics or data science researching the physics and operational data of a physical object or system in order to develop a mathematical model that simulates the original.

The developers who create digital twins ensure that the virtual computer model can receive feedback from sensors that gather data from the real-world version. This lets the digital version mimic and simulate what is happening with the original version in real-time, creating opportunities to gather insights into performance and any potential problems.

A digital twin can be as complex or as simple as you require, with differing amounts of data determining how precisely the model simulates the real-world physical version.

The twin can be used with a prototype to offer feedback on the product as it is developed or can even act as a prototype in its own right to model what could occur with a physical version when built.

What Challenges have been Solved?

Since it can be used across a wide range of industries, from automotive to healthcare and power generation, it has already been used to solve a large number of challenges. These challenges include fatigue testing and corrosion resistance for offshore wind turbines and efficiency improvements in racing cars. Other applications have included the modeling of hospitals to determine workflows and staffing to find procedure improvements.

A digital twin allows users to investigate solutions for product lifecycle extension, manufacturing and process improvements, and product development and prototype testing. In such cases, a digital twin can virtually represent a problem so that a solution can be devised and tested in the program rather than in the real world.

Who Invented It?

The concept of digital twins was first put forward in David Gelernter’s 1991 book ‘Mirror Worlds,’ with Michael Grieves of the Florida Institute of Technology going on to apply the concept to manufacturing.

By 2002, Grieves had moved to the University of Michigan when he formally introduced the digital twin concept at a Society of Manufacturing Engineers conference in Troy, Michigan.

However, it was NASA that first embraced the digital twin concept and, in a 2010 Roadmap Report, John Vickers of NASA gave the concept its name. The idea was used to create digital simulations of space capsules and crafts for testing.

The digital twin concept spread further still in 2017 when Gartner named it one of the top 10 strategic technology trends. Since then, the concept has been used in an ever-growing array of industrial applications and processes.

When to use It

A digital twin can be broken down into three broad types, which show the different times when the process can be used:

• Digital Twin Prototype (DTP) - This is undertaken before a physical product is created

• Digital Twin Instance (DTI) – This is done once a product is manufactured in order to run tests on different usage scenarios

• Digital Twin Aggregate (DTA) – This gathers DTI information to determine the capabilities of a product, run prognostics, and test operating parameters.

These over-arching types can offer a variety of uses including logistics planning, product development and re-design, quality control/management, and systems planning.

A digital twin can be used to save time and money whenever a product or process needs to be tested, whether in design, implementation, monitoring, or improvement.

To be continued in, #31 - What is Digital Twin? - 2

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