Gartner placed digital twins at #5 on its Top 10 list of technology trends for 2017, predicting that in the next three to five years, billions of physical things will have twins in the digital space. The effect of this on industry could be staggering — digital twins are predicted to improve product development, shorten process cycle times, reduce maintenance downtime, and much, much more.
To help you better understand digital twinning and the opportunities it provides, we’re kicking off a series of articles that will introduce the basic concepts of digital twins and then look at how companies are using them to improve their engineering operations. Here, we’ll start at the beginning, by defining the digital twin and taking a brief foray into its history.
Digital twin definition
A digital twin is a virtual model of something in the physical world, such as a product (a car), a process (a production line), or a facility (a processing plant). Digital twins are frequently referred to as bridges between the physical and the digital.
What makes a digital twin different from a drawing, schematic, or other more traditional representation is that it’s dynamic. Digital twins don’t just represent the physical system itself, they also represent all of the information embedded in that physical system. As such, they change in response to contextual information, which means you can use them to assess how changing contexts (e.g., different inputs, environmental factors, the wear and tear of aging) will affect the physical product.
Another crucial aspect that sets a digital twin apart from drawings and schematics is that it allows stakeholders across the organization to have access to the same real-time picture of the physical asset. You don’t have to worry that one department is working with version 9 and another with version 10. Your digital twin is always up to date.
Here’s one perspective from Chris O’Connor, the general manager of IBM Watson. As he explains in this YouTube video, a digital twin can help you optimize a project across its entire lifecycle:
- During the engineering phase, a digital twin allows engineers to test different designs and expose them to different contexts in advance. This means they can find any inefficiencies, mistakes, and other opportunities for improvement before any time, energy, or money is spent on production.
- During the build phase, a digital twin helps you improve efficiency, quality, and yield, for example, by understanding the effect of a production change.
- Finally, digital twins also facilitate the operations phase. Products, plants, and processes age, and as they age, things drift. A digital twin can drift as well, which helps you understand, adapt to, and correct the changes happening in the real world (e.g., planning maintenance schedules).
Origins and early uses of the digital twin
Although the digital twin is experiencing a surge in popularity, the idea isn’t new. It was introduced in 2002 at the University of Michigan by Michael Grieves in a presentation on the formation of a Product Lifecycle Management (PLM) center. At that time, the digital twin was conceptualized as a virtual mirror that would enable engineers to better understand the behavior of complex systems in order to mitigate “unpredictable, undesirable emergent behavior.”
One of the first big adopters of digital twins (even before the term was coined in 2011) was NASA. Their objective was to solve the problem of developing and maintaining systems they wouldn’t be able to monitor physically. The agency still uses digital twins to develop systems and equipment.
John Vickers, NASA’s principal technologist in the area of advanced manufacturing, explains:
The ultimate vision for the digital twin is to create, test, and build our equipment in a virtual environment. Only when we get it to where it performs to our requirements do we physically manufacture it. We then want that physical build to tie back to its digital twin through sensors so that the digital twin contains all the information that we could have by inspecting the physical build.
Now, hopefully, you have a better idea of what a digital twin is and you’re starting to grasp why Gartner named it as one of the biggest tech trends of the year. In the next article, we’ll look at the relationship between digital twins and the Internet of Things.