Digital twins are a foundational Industry 4.0 tool and are being leveraged by education and industry to design new systems, improve processes, and perform cutting-edge research in education.
A digital twin is “a virtual model designed to accurately reflect a physical object,” says IBM. It’s a digital version of a physical system used for design, testing and process optimization.
While they’ve been around for decades (Apollo 13 had its own digital twin), the adoption of these tools is growing at an exponential rate in the last few years. This is largely due to to major brands launching digital twin platforms – Microsoft Azure, Unity Industrial Collection, IBM Digital Twin Exchange and others, as well as a plethora of accessible artificial intelligence and machine learning tools that make the deployment of digital twins easier and more robust.
Rockwell Automation recently added Emulate 3D to its solutions portfolio. In an episode of The TechEd Podcast, Rockwell’s VP of Global Portfolio Engineering Andrew Ellis described Emulate 3D: “That’s our digital twin that allows us to connect to our controllers so I can test out code, build my twin before I build [the physical system], and then deploy [it]. I can use it for commissioning.”
Sometimes the term digital twin is used synonymously with simulation, but there are some unique differences. Simulations are confined to the virtual world – they’re great for modeling and testing system design, but that’s where their application ends.
Digital twins, on the other hand, have a two-way data relationship with their physical counterpart. They can be used for modeling and testing, but once that physical system is deployed, it can also be outfitted with smart sensors and devices that feed data back to the digital twin for analysis. This enables engineers to detect anomalies in the physical system that aren’t behaving as designed. It also enables them to make changes to the system in the virtual environment, test it using the available data, and refine the new design before re-commissioning.
Unity, the world’s leading 3D tool developer notes, “a digital twin ingests data and replicates processes so you can predict possible performance outcomes and issues that the real-world product might undergo.” They’re far more robust tools than simulation alone.
Commissioning new automation lines (a more common occurrence in today’s tight labor market) is an arduous, involved process. There are so many moving components that being able to test a system design and remove flaws before deploying it on the shop floor is a huge advantage.
Ian McGregor is a Global Emulate3D Business Development Manager for Rockwell Automation. He wrote about the challenges manufacturers face when designing new systems: “It comes down to meticulous up front planning – before metal is cut, or existing lines disturbed. One thing is certain. Learning of problems with controls integration, line sequencing or bottlenecks after machines are built or lines reconfigured is not the best time. Too often I’ve seen this turn into installation delays, and worse, broken promises.”
Matt Kirchner, Host of The TechEd Podcast and 23-year manufacturing exec, agrees. “The scariest day in the life of a manufacturing engineer,” he says, “is the day that you change the process on the shop floor. Because if you change it, and you get it right, and you improve throughput, or you improve yield, you’re a superstar, right? And if it doesn’t work, all eyes are on you. That is the worst day of your life is the day that you you mess up the system. And now you’ve got lead time issues, you’ve got customers that need product, and you’re not able to produce it. And it was all because you had a miss on a technology change.”
But Matt goes on to talk about how digital twins come in and solve those problems before they ever occur. “What digital twin software allows us to do is really work all of those mistakes out ahead of time so that when we do turn that into a physical asset on the shop floor, so many of the things that we may have had to do in the physical universe we can actually do in the cyber universe, and we can we can work on all those challenges. And then we can connect that to the cloud, and gather data from it and allow us to predict the future.”
The obvious application for digital twins is in manufacturing and industrial processes, which we’ve already explored. But like other Industry 4.0 technologies, digital twins are being used across nearly every sector of the economy.
PTC shares a unique use case in their State of Digital Twin 2022 Report. In April 2021, an 80-year-old bridge in Norway was on the brink of collapse – a fact engineers only knew because of the digital twin that SAP had helped design for the Stavå bridge. The physical bridge had been outfitted with smart sensors and IoT-enabled monitoring devices that fed data back to a digital twin in real-time. When the ever-running algorithms predicted a potential oncoming collapse, the authorities were able to divert traffic and shut down the bridge before disaster could occur.
Here are some other unique use cases for digital twins:
University: The University of Wisconsin-Milwaukee’s Connected Systems Institute is an excellent example of digital twins in education. The university has developed strong partnerships with industrial brands like Rockwell Automation, Endress + Hauser and FANUC who co-developed an authentic automated manufacturing system housed in the CSI called the Manufacturing Test Bed. The system features a fully functional production line loaded with Industry 4.0 technologies, control systems, industrial robotics, and IT/OT technologies from brands like Cisco, Dell and Microsoft.
Next door to the Manufacturing Test Bed is the Digital Twin Lab, featuring a digital replica of the physical system. IIoT devices pull data in real-time from the physical system and load it into the digital twin. Students have access to the digital twin, where they can use simulation and programming software from Ansys and PTC to simulate new processes and design changes in a virtual environment.
Technical College: Gateway Technical College has one of the most advanced Connected Smart Manufacturing systems in the country. Taking up a full lab, the system includes a full Industry 4.0 mechatronics line, autonomous mobile robots, industrial robot arms, CNC machining simulator, and a suite of IIoT enabled sensors and devices that regularly feed production and equipment data to specialized software. The data is visualized in screens along the wall.
David Aguirre, IIoT Professional at Gateway, has developed digital twins of the systems in this lab (and others at the facility). He wrote about using FANUC’s MT-LINKi data analytics software to extract and visualize system data in real-time in The Power of the Industrial Internet of Things (IIoT) and Data Analytics.
That’s just the tip of the iceberg. Digital twins are gaining traction in education and research. FANUC’s Roboguide software allows learners to test and refine their robotics programs before implementing them on live robots. Quanser’s QLabs software enables engineering students to control and test 3D models of their physical lab experiments in a virtual environment using Python, ROS and MATLAB Simulink. These virtual environments are designed to react identically to the physical environment. This is especially fascinating for systems like the self-driving car studio, where students are doing cutting-edge research on autonomous vehicle technology.
The takeaway is pretty clear: digital twins are an incredibly powerful tool being deployed by every sector of our economy to design, test and optimize systems of all kinds. The sooner we can get this technology into the hands of our students and learners, the better.