It’s the sixties, and NASA has a problem. John F. Kennedy tasked them to put a man on the Moon. Further than anyone (or anything, at the time) had ever gone before. The engineering challenges were enormous, and one of them was this: how do you operate, maintain and repair a machine that was millions of kilometers away, that you cannot physically access and that you cannot even see?
NASA started developing a system that would mirror its counterpart in space. It was the precursor or what Michael Grieves called a digital twin in 2002. Come 2017 and Gartner has placed digital twin technology in its top 10 strategic technology trends. Technology experts estimate that billions of things will have digital twins over the next few years. But what exactly are digital twins, how are they used in different industries, and how does VR improve a digital twin? Read on to find out.
What is a Digital Twin?
As per IBM’s definition, a digital twin is a virtual representation of the elements and dynamics of how an ‘Internet of Things’ device operates. Let’s go through that definition, from back to front.
An Internet of Things (IoT) device is a product or process that can send and receive data. This product can be anything: from an Amazon package with an RFID tag to a servomotor with sensors attached to it. It can also be a process: a manufacturing chain or shifts of the employees in a factory. An IoT device can even be something like a building, where variables like temperature, airflow, and others are measured.
Next in the definition is ‘a virtual representation of the elements and dynamics’. By this, IBM means that a digital twin is a replica not just of the material that the IoT device is composed of, but also of its flows. As such, a digital twin is not a snapshot of the physical device at one point in time, but a continuous, real-time, and digital monitoring of it. What you decide to monitor is up to you, but the idea is that you monitor every possible variable. Otherwise, your digital replica will be inaccurate and can lead you to false conclusions.
So a digital twin is an exact, complete, and digital replica of a physical device or process that can send and receive data. But what is it good for?
Industry Examples and Use Cases
Big manufacturing companies like Siemens and General Electric use digital twins to make their factories more efficient. Because each factory has a digital twin that’s completely identical, engineers can try out new ideas without taking up precious resources or without running the risk of messing up things in the factory.
If the engineers believe a certain type of product could be produced faster by moving this part of the assembly line closer to that area of the factory, then they can simply try that out in the digital twin and see the effects of that change on the manufacturing rate of the product. If the manufacturing rate goes up while the quality stays the same, then they can go ahead and implement those changes in the actual factory.
Formula 1 cars have digital twins. So do wind turbines, jet engines, and even mass-produced goods. More and more companies are asking for digital twins of the products they’re thinking of buying, so they can understand how the product works and whether it would do what they want it to do.
In healthcare too, digital twins are increasingly used. Not only can a digital twin recreate an entire hospital and improve variables such as patient flow, but a single patient can have a digital twin too. Surgical procedures or the effects of certain drugs can be tested and monitored digitally before they’re implemented; something that could save a significant amount of lives.
How Can VR Improve a Digital Twin?
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.
The Pros and the Cons
A digital twin helps companies save time and resources. It’s a tool to experiment, to optimize, and to understand what’s slowing things down. But for all its benefits, digital twins are still very difficult to implement.
A digital twin needs to be able to receive a tremendous amount of data. To give an idea: a single connected car sends 25 GB of data to the cloud every hour. That’s a lot of content for any technology to continuously receive. The algorithms of the digital twin need to be able to make sense of this data, as well as understand the connections between different types of data.
These algorithms also need to be able to adapt to new data, as no physical object lives in a vacuum. The external environment and the inner workings of the physical object will change as time goes by, and so the algorithms of the digital twin need to adjust to this reality too.
Luckily, technologies such as 5G and advanced algorithms make digital twins of increasingly complex products and processes a reality, even if you don’t have billions of dollars in revenue. Combine this with the fast progress of VR and AR visualization technology, and it won’t be long before digital twins will become a reality for most companies.
