Meet the new you: rise of the digital twin from products to people

For a term that right now sits at the very top of the Gartner Hype Cycle the digital twin idea deserves to be better known than it is. Gartner places the digital twin in the digitalised ecosystems trend alongside better known technologies like blockchain and the Internet of Things, but it has certainly not yet entered public awareness in the same way as buzzwords like artificial intelligence, driverless cars or even quantum computing.

Do not for one minute think that the digital twin is all hype. It’s an engineering model already being used to great effect by thousands of companies in the industrial maintenance area, and that’s just for starters. Gartner predicts millions of digital twins will emerge in the next few years. Soon everyone will be interacting with digital twins without really knowing, as it’s something that can take place behind the scenes as far as consumers are concerned.

Some complain it’s a vague, woolly term and nothing new, but to me it’s evolved into a meaning that’s pretty clear: a virtual mirror of a real thing. But it’s so much more than a simulator. It’s a bit like the portrait of Dorian Gray (with a spoiler alert for those who have not seen or read the Oscar Wilde classic story) but it ages just like the real thing rather than instead of it. It may be built from original design data, but a digital twin is for each product unit rather than just a simulation of the general product design. Crucially, the digital twin changes to reflect the real entity, using big data from sensors on the real product to make it ‘experience’ everything the real product goes through. 

This provides a powerful new model for predictive maintenance but also for maintenance and training using AR. Aggregated individual product experiences provide vital information from the field for the manufacturer and for product designers and developers. Ideally, the digital twin lives from cradle to grave: from when the product is designed to when it is recycled at the end of its life.

Each product instance will have a digital twin, but so will each component, and so will each system it is a part of – even if it’s a whole city. The model seems to have no bounds to me. It can be applied to just about anything physical that is wired for data with sensors, even if the initial model is based on observations, like the biological, rather than design.  That could one day include digital twins for you and me. If a motor can be wired with sensors to send data to a digital twin to predict failure, why not a human being? Perhaps our digital twins will be used to spot potential heart problems or by using them as sandboxes, to try out various medicines or develop personalised treatments. Or perhaps they will just tell us what we already know at the start of a new year: that we need to eat more healthily and exercise more.

One day, you may have your own digital portrait in the attic, and while it may not stop you getting older it may help to keep you healthier.