A digital twin is a digital representation of something. Often, it is a digital representation of a physical object, but in more general sense it can represent a complex system that may consist of a combination of hardware, software, humans and environment. Such as a production process, for example. Or an industrial robot, a cat, a human. Or just air. Anything that is of interest of keeping track of, predict changes, optimize and play around with. To create a digital twin of something physical, we make use of sensors and actuators to tap into the data and control capabilities. Or, if it’s a binary twin of your smile with the only mission of tracking it, we can make use of cameras, serotonin level in your body or just ask the twin of your teeth if they can see the light. In this blog we will talk about the reasons for having a digital twin and what to use it for.
1. Always reflecting the current state
Checking up on your car or a fleet of cars, production plant, wind turbine, wine yard or mining facility may not always be easy because of the complex mechanics, physically distributed things and hard-to-access locations. In addition, regular health-checks are not always good enough when you need to be on top of things as they happen, and to be able to prevent anything unwanted happening. Observability is a pre-requisite for a successful data-driven management of whatever you want to manage.
2. Useful for what-if scenarios
First there were models and simulators. Then they evolved to twins. One can do a lot with a model but often it’s static and needs to be adjusted from time to time to reflect the reality. Twins evolve together with the reality in a data-driven fashion. Communication with the twin is often implemented to be bi-directional meaning that not only the reality makes an effect on the twin, but also changes in the twin effect the reality, like a voodoo doll. And as much as we all love experiments we normally do them in experimental environments and not in live systems. The fine property of a digital twin is that at any moment one can take a snapshot of the latest state and save it as a model to run experiments on. And the classical type of experimentation is what-if scenarios. What if I change an ingredient in my production process? What if I de-centralise my organisation? What if I replace a supplier? What would it imply, both in a short- and long-run?
3. Can be used for simulations
As in the previous paragraph, taking a snapshot of your twin gets you a perfect latest model to experiment with. On can also run simulations, fast-forwarding the development of things along the way. Imagine you have a model of a city that you let evolve by itself at a high pace. Will the city double its size in 20 years? What would the pollution levels be? What the would the GDP be? Almost like SimCity (for those of you who remembers) but based on a latest snapshot of a real city.
4. Can be used for property checks and decision support
When working with digital twins we are in an open world assumption. As soon as we have taken a snapshot of a twin and created a model of environment we are in a closed world assumption, which is an approximation of reality but so much nicer for formal verification community as system properties can be formally checked and guaranteed. One can, for example, check that the level of greenhouse gas emissions in a production plant never exceeds a certain threshold. Of, it it actually does, one can get an explanation of the root-cause and a suggestion of how to act differently.
5. Abstract away the details
The beauty of abstraction is that one can focus on what’s vital for you. This is obvious when doing an abstraction of a piece of software. If your level of abstraction is too high, you may miss some important properties. If it’s too low, then you are not far from the original piece of software, and drowning in its complexity. Similar with systems that are more than just software. If it’s a production plant and you only focus on it’s productivity at any price, you can omit the cost monitoring from your twin. Or, if you don’t bother about contributions to climate change you don’t need to collect that data either. But we believe that you do care about both the cost and climate, so let’s make sure we keep focus on them.
6. Can control the physical twin
As we said before, the relationship with the digital twin is bi-directional, like with a voodoo doll, but with a positive twist to it. If you have branched out a model out of your twin, experimented with different what-if scenarios, simulated 10 years ahead, checked all the vital properties and converged on a necessary change in your system, often you can implement it though the twin by actuation. You can, for example, limit speed of your autonomous trucks to have more positive effect on safety, of decrease the temperature of your production facility to improve your carbon footprint. And, given that you have connected supply chains, you can also tweak ingredients in your production line or even make upgrades to your hardware. Don’t experiment on your workforce though – there we still recommend human touch.