What is Digital Twin technology and what value does it bring?

By Oliver, Eastpoint Software on 31 March 2021

The definition of what is a digital twin is a heated topic.

The term digital twin is often used to describe an evolution of IoT solutions where sensory data is captured and stored digitally about a physical asset or process, and that digital data is represented in a meaningful way to do something actionable, in an automated way.  

The definition I most resonate with is from Advanced Manufacturing Research Centre in the UK:  

“Live digital coupling  
of the state of physical assets or process  
to a virtual representation  
with a functional output” 

This definition implies that for a technology solution to be considered a digital twin it should:  


  • Have a means to monitor physical assets or processes digitally (e.g. with sensors connected to the internet) often enough to be considered “live”  
  • Have a means to represent the digital data (e.g. digital data stored with context of the physical asset or process)  
  • (Most often) have a means of visualising the state of the physical counterpart, and the solution must do something useful.    

What is the value of a digital twin?

Where applicable, digital twin allows for optimising the value generated by a technology solution. Value can be in reduction of cost, time and human effort required to achieve optimal output against complex processes.

Key benefits come from the fact that it is often cheaper and quicker to experiment, analyse and iterate in a digital space (e.g. using a digital twin’s data) over doing so in the physical space, or on the physical item or product.

For example, if one was to manufacture a new set of headphones by having the entire product design digitised and experimented on with different designs through digital simulations, with each simulation for example measuring audio quality, designs can be iterated much quicker to yield optimum results, compared to manufacturing numerous prototypes and testing them physically.  

During manufacturing stage, the physical prototype’s performance would be validated physically, and the data from that validation could be fed back to the simulations to seek further optimisations.  

By conducting simulations or analysis in the digital space, the designer can get to meaningful results faster, with fewer physical prototypes – this leads to reduced time to market, and reduced R&D costs. That’s the promise of digital twins in this context.

To understand this further, the Centre for Digitally Built Britain (CDBB) have created a “Digital Twin Toolkit” aimed to help businesses understand the value of digital twin, and also to build business cases for digital twins. See more at this link:

What is digital twin in manufacturing?

Digital twin is often associated with manufacturing because the first mention of it came in 2002 from the manufacturing industry.

In ths context, it was proposing to look at product lifecycle management by capturing all digital data about a physical product, and then use the digital data to feedback into the product’s lifecycle.  

For example, in manufacturing lines each of the physical components being created would have a digital counterpart - it’s “digital twin” - where all the data about the physical component is stored digitally, and all that digital data is meant to represent the complete state of the physical component being manufactured.  

The digital data can then be manipulated and experimented on safely (compared to doing the same thing on the physical components) to give new information which can influence the physical component and the processes surrounding it during its lifetime.  

What is a digital twin used for?

Digital twin development can be applied to so many vast scenarios, including anything that has a physical component that has processes managing it.  

One example is predictive maintenance in the heavy engineering industries. They may have real, physical aging assets that need attention for maintenance at unpredictable timings, and it is very costly when the assets are damaged.

By having numerous sensors and physical inspection reports digitised to store and represent the assets of interest with a digital twin solution, they can harness the power of simulation and AI, to constantly update the knowledge of the physical state of the assets, predict future performance and enhance visualisation for engineers.

This can lead to appropriate interventions in a timely manner that ultimately lead to reduced down time and therefore cost savings.

It doesn’t have to be engineered and manufactured components – people, documents and processes can be modelled and monitored as a digital twin, so the use cases are very vast.

Some of the finest use cases are for managing physical infrastructures, for example smart cities.  

How do you create a digital twin?

There isn’t one way to make a digital twin, but certain things do need to be in place.  

1. Technology to digitise the ‘state’ of the physical things you care about  

This could be various sensors connected to internet, feeding telemetry data live

2. A digital infrastructure that captures all the data, and store that with appropriate context

3. A digital infrastructure that enables doing something useful with data representing the physical world

For example, conducting a virtual simulation on what would happen to air quality in a room if x number of extra people were to join and stay in a room for the next y hours - and then sending out a warning to appropriate places if the result was below acceptable levels.

Or visualising the flow of traffic predicted in the next x hours, and looking at the effect on air polution near pedestrian areas, so that the operator can take appropriate action.

You can get lots of good insights on this topic from:

One key takeaway from the Gemini principle stated in the above link is:

Make data accessible so that digital twins can integrate with one another to harness greater use of data for public good.

This should be at the forefront of every digital twin creator’s mind.

At Eastpoint, we focus more on the digital infrastructure; and we like using Microsoft Azure solutions that greatly reduce the risks and delivery time needed to have a scalable and robust solution that creates a digital twin solution.  

What does a digital twin consist of?

Generally speaking:

  • A collection of connected devices and automated processes, that are...
  • integrated with a digital infrastructure that collects and stores all the data, and...
  • able to represent the physical asset digitally through visualisation

Technologies including IoT, virtual simulations, artificial intelligence (AI) and 3D visualisations with augmented/virtual reality (AR/VR) can be part of the digital twin solution.

Digital twin development 

If you are exploring digital twin to improve, optimise, report, predict, or any project with a digital twin component, we are very keen to hear from you.

We are currently working on an ambitious 5G digital twin project for the energy sector and have excellent software expertise for digital twin development.

Call us on 01223 690164 or email us at