- A brief definition of digital twin
- How the tech is being used to create concise and accurate predictive models
- Walking in 360-degrees, surveillance and monitoring takes on a whole new meaning
- how accuracy in digital twins comes at the cost of a never-ending data flow
What is a digital twin?
Proposed by Michael Grieves at the University of Michigan, the concept of the digital twin has been in use since 2002. However, it’s only gained recognition as a realistic opportunity in recent times.
A digital twin simply refers to a virtual replica of a physical product or assets. This replica is updated as regularly as possible or in real-time.
The constant updating is meant to keep up with the real-world counterparts and any changes that it may go through.
This is done in order for the digital twin to be as similar to the physical counterpart as possible. Therefore, it might be successfully used for a range of purposes which includes analyzing previous results and testing new strategies.
Test before you invest: a digital replica
You might ask why to go through all the trouble of creating a virtual duplicate of a pre-existing structure or area. The answer is very simple, to create an environment where changes can be made with almost identical results in the physical space.
Experimentation is a vital part of the developmental process. However, it can be a really costly endeavor. Not only is it financially demanding, but it can also be time-consuming.
With a digital replica, however, new solutions can be tested and simulations can be run with quick edits.
Digital twin helps companies to make changes to existing production equipment, reducing downtime to an absolute minimum. It is created with identical data and layout as the original, allowing experts to remotely access vital information about the physical asset by simply working on the digital twin.
It allows alterations and updates to be planned in exact detail for off-site testing.
After the testing has been done, instructions can then be sent to those with access to make the physical changes. If for instance, the experiment does not produce the desired results, the experiments would not have been performed at the expense of physical resources.
For instance, in a production line, an ineffective link can be refined and tested without having to shut down the entire process and incurring additional costs.
But that’s not all, while you may be able to use the digital twin for predictive analysis, you can also use it for monitoring and situational awareness for the existing structure.
Here is where adding either VR or AR can be said to be putting wings on a tiger.
Currently, digital twins are 3D-models represented on 2D-screens. VR allows users to immerse themselves in the environment of the digital twin. It gives a more visceral impression, which helps better understand the dynamics of the digital twin (and so also of its physical counterpart).
AR has its place here too. When you’re physically close to a machine, its digital twin can be overlaid on top of it, so you can visualize the machine’s inner workings and understand its data flows. This makes for faster and more effective decision-making.
Creating a predictive model
First, let’s talk about what impact adding VR or AR technology to a predictive model would induce.
These technologies have primarily been used to create or enhance reality but in the case of a digital twin, we would be talking about being able to see the outcome or changes while performing modifications to the digital twin environment in real-time.
Combined with highly advanced machine learning technology, it is possible to have real-time breakdowns of structures, market, public spaces or literally anything in the real world and create a digital twin of it where experimentation and adjustments can be made without affecting the real structure.
Real-time 360-Degree view with AR/VR
But as fascinating as being able to create predictive models are, nothing beats the ability to have an uninterrupted 360-degree free-flowing few of a given structure. This is where VR and AR technology merged with Digital Twins really shine.
Let’s paint a picture.
JFK International airport is one of the business airports in the world seeing millions of passengers go through its facilities each year, just the logistics of managing such a huge space is a massive undertaking.
But what if you created a digital twin of the Hangers, Terminals and others with the ability to freely walk about the structures, either in VR or using AR glasses/devices.
Your employees would be able to see all the connections and faults with electrical, heating or power installation in real-time. They could easily direct staff to the exact location they are needed, fixing bottlenecks quicker. All this without having to move from one central location.
Not only do you increase security, handle crisis faster and more efficiently but you also streamline the operations of the airport such that it can handle all sorts of issues within the shortest possible time.
Yet it should be noted that creating a digital twin for any establishment is not a small or light undertaking. The amount of data to be accurately processed and inputted into the system are usually massive.
Hence, when pairing Digital Twins to the VR and AR industry, we usually see that it’s the enterprise users that are making use of this technology. Adding machine learning algorithms and AI into the mix usually leaves for higher efficiency and overall productivity.
The bright future of digital twin tech
On average a digital twin saves a company an estimated 20% to 30% of development costs. For a threshold cost of €50,000, it remains a viable option for developing Hi-Tech systems.
However, as the digital twin technology progresses, the economics of scale will develop. This will cause a reduction in the threshold cost, broadening the application of the digital twin technology to a wider stage.
As positive as all these sounds, there is still a way to go before we can say the tech is fully matured.
We should not forget that digital twins take up a lot of data and more is being generated each moment the twin is in operations else it would be of no use having aged or out-dated information as a twin has to mirror reality.