As processing power, storage and memory have become commoditised, the opportunity to use technology in new ways has expanded. One of the tools being used by many companies is a digital twin. These digital representations of real-world objects and processes are giving businesses a way of predicting when something will break down and helping them find ways to improve efficiencies.
What is a digital twin?
A digital twin is a digital representation of a real world object or process.
For example, let’s say you manufacture a widget and there’s a step in the process that requires a high degree of precision. You could create a digital model of that step – the digital twin – that is constantly updated with data from the actual process. You can then monitor the digital twin and play with the model to see what would happen if production volumes were increased or some other condition was altered.
Alternately, if you make a product, you could create a digital twin of that product. Tesla does this. It retains and monitors a digital twin of every car it makes.
The idea of the digital twin isn’t new – Forbes reports that it was first coined in 2002 by Michael Grieves at the University of Michigan.
What do you need so you can create a digital twin?
Digital twins need data – lots of data. And then you need somewhere to store that data and enough processing power to make use of it.
We now live in an age where computing power is readily available in massive quantities through cloud services and data collection through IoT sensors makes it easy to collect everything you need to create a digital twin.
So, while the idea of the digital twin isn’t new, our ability to apply it broadly is a recent phenomena.
Why bother with digital twins?
If you think back to high school science classes, you’ll recall the idea of a controlled experiment. You start with two or more as identical as possible test subjects and treat each one differently, keeping one in its original state. You could then measure the effect of your experiment by comparing the altered subjects with the unaltered one.
Digital twins give businesses the opportunity to do the same thing. They can experiment with processes and products safely to find better ways to delver outcomes for their customers.
Tesla’s digital twin set up is a good example. By constantly collecting data using the sensors in the car they can detect problems, test software solutions on the digital twin and then apply them to vehicle through a software patch.
With digital transformation now driving the pace of change in business, being able to efficiently experiment and make changes to the way you work is a massive advantage. Digital twins can help use the data you’re collecting so you can turn it into actionable insights.
The applications for digital twins aren’t limited to manufacturing. In healthcare, smart bandages can collect information where doctors can model different “what if” treatment scenarios based on data coming from a specific patient.
Are digital twins a big deal?
In a word – yes.
According to research from IDC, almost a third of the top 2000 global companies are using data from digital twins.
We’ll see digital twin technology in almost every facet of business life. From measuring processes to monitoring equipment performance through to healthcare, digital twins will allow people to better understand the performance of almost any system and process and safely experiment with how to improve it.