Episode 77 of Razorleaf’s Stay Sharp podcast, Mastering the Digital Twin Terrain, is the start of a new series in which co-hosts Jonathan Scott and Juliann Grant will dig into foundational concepts. Their goal is to explore what “digital twin” means and how they can be meaningful to your company—recognizing from the start that there are many different terms related to or describing the concept. In this first series entry, Jonathan and Juliann cover an overview of some of the key concepts involved in digital twins and lay out some of the paths future conversations will travel.
Defining Terms
The co-hosts acknowledge at the outset that the term “digital twin” can mean a lot of things to a lot of people, but they agree it mostly represents a digital item that matches or aligns with a physical item. They also discuss a variety of relevant terms, including two that together make up a digital twin: digital shadow, which is moving data from the physical representation to the digital representation, and digital surrogate, which is moving data from the digital to the physical. Jonathan explains, “When you have the case that data is flowing from the physical instance back to the digital model, and the digital model is being used somehow to control the physical instance, you have some kind of closed loop. That’s where I think people say, yes, that’s a true twin. That is really a digital twin.” A virtual twin, on the other hand, Jonathan sees as more of a digital representation or prototype of the future physical thing they want to build.
Digital Twins Beyond Products
After starting by defining a product digital twin, Juliann and Jonathan expand the scope of the twin concept. Juliann brings up the intersection of product and process—a process digital twin. Those can include how a product is made and what the process involves to achieve the specifications it needs to meet. Jonathan notes, “If you could create a twin of your process to include all these parameters, then you could predict the outcome on the product that you’re making. Process twins are a thing.” The pair agree if you multiply that process twin by a large number, you could create a factory digital twin—even before you try to build one. “That concept of a factory digital twin,” Jonathan says, “I think probably relates to what a lot of businesses are hoping they can get to. If I can understand all of my operations and everything I do to create my product, I can create products quicker, more efficiently, more reliably.”
The Purpose of Digital Twins
The reasons why people might employ digital twins are a lot more difficult to define than the terms. Some people think digital twins will help them do business better, understand their product better, help them build a better product, prevent breakage, or improve the next version. Jonathan adds, “Sometimes I think they mean that it’s going to help me manage my product better—so I know what’s going on with the physical one out in the field—and help me react and have my business react better because I’ve got more information.”
“To me, that’s the whole point of having these digital twins,” Juliann says, “to get some regular feedback on a product in use so you can at least make sure you prevent problems. That whole preventive maintenance thing.” Jonathan emphasizes that a key piece of a company’s digital twin process—even of their digital transformation journey—is knowing why you’re doing it. “What’s the purpose that you’re building out some kind of digital twin? Because that’ll really tell you what you need to do with it.”
Another reason you need to define why you’re making models of the real world is because if you twin everything, you’ll end up with more data than you can handle. “You have to make some choices, and in some cases maybe trade-offs between what you can collect, what you can know, what you need to know, and what you want to get the output that you need,” Jonathan says. “It always comes back to that purpose. What do you need? What are you trying to accomplish?”
Learn More About Digital Twins
The full podcast contains more discussion and details on a variety of topics, including the definitions of a digital model, digital instance, and digital aggregate, why product lifespan will influence what you need in and from your digital twins, why data management, simulation data management, and analytics may be critical elements, and more.
Check out the full conversation in Stay Sharp Episode 77: Mastering the Digital Twin Terrain, and join us each week for a new podcast.
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