Not long ago aerospace was the principal user of digital twin technology, but in 2020 even small machine shops drive Lean initiatives by assembling digital tool assemblies in the cloud.
Image from Giphy
Posted by @ge
We tend to presume that digital twinning is something that automotive and aerospace manufacturers use to improve their end-use products. But the fact is that digital twins have evolved into much more than the exclusive roles they play at the end of the supply chain.
A Brief History of Digital Twin Technology that is Actually Brief
Image from Giphy
So many great ideas come from sci-fi novels, and digital twin is no exception. David Gelernter’s book Mirror Worlds (1991) first posited the simulation of the real world as digital reality. That is post Star Wars. Post Star Trek. Post Warp Drive and Light Saber.
It was different than so many other digital/real concepts to come out of the 90s because unlike the others it was fundamentally about simulation. Most other ideas, such as the Matrix, or even Second Life, revelled in the significant differences you could create when reconstructing the material world in 1s and 0s. That couldn’t be more different than the ultimate goal of a digital twin, which is to become so similar to its doppelganger that it can then be used to predict what will happen in the real world.
But it was only eleven years until Michael Grieves presented the digital twin to the Society of Manufacturing Engineers in Troy Michigan, leaving Star Wars’ warp drive in its astral dust. He conceived of digital twin as an underlying principle of Product Lifecycle Management (PLM). If you could create a digital simulation of a real world object, then you could run tests on that digital object and use the results of those tests to proactively choose better maintenance schedules or even to make better products.
Initially the idea was impractical due to severe IT constraints. But gradually it was implemented by what you might call high-tech, high-budget applications (aerospace and automotive). That brings us to about five years ago, when GE proudly posted the gif at the top of this post that shows just how much data comes from their turbines.
Yes that’s right. September 2015 was when GE had its moment of accomplishment. Now, only five years later, it’s our turn.
Digital Twin for Tooling
Last year was a true breakout for this tech, especially for companies involved in IoT.
“Thirteen percent of organizations implementing the Internet of Things (IoT) projects already use digital twins, while 62 percent are either in the process of establishing digital twin use or plan to do so…” (Gartner Survey Reveals Digital Twins Are Entering Mainstream Use, Feb. 2019).
That is a huge jump from 13% to 75%. That’s like what happened with hipsters in New York City. This is happening NOW. Literally 62% of IoT projects were building digital twins one year ago.
But IoT projects does not even begin to cover all the organizations mobilizing in our industry. When MachiningCloud asked machining pundits what would be in store for us in 2020, many discussed Lean Principles, the need to increase efficiency and reduce expense. They also discussed specific applications that would help machine shops become even more efficient in 2020. But Gene Granata, Product Manager at CGTech directly applied the digital twin concept to tooling.
« Accurate toolpath simulation is key to eliminating potential problems in manufacturing, but it requires accurate twinning of the cutting tool assemblies and the CNC machine tool,” Granata said. “Obtaining and utilizing these models will continue to be an excellent way for shops to improve their manufacturing operations this year.”
If you think about it CAD/CAM laid the groundwork a long time ago. Whenever you run a toolpath simulation or verification feature you are applying the digital twin concept. And you are sparing your shop all that botched programming that would have led to a ruined part. Every amendment is a save.
And yet, there has been a critical difference between this and the stereotypical digital twin. Communication. No sensors to connect real part with digital representation. No knowledge of past toolpaths and results. These fundamental elements of digital twin technology have been absent.
Now you can see them coming together in a connected set of digital tools. MachiningCloud already allows you to build your tool assemblies in the cloud and export/import that information in CAD/CAM. Our users literally source their real-world and digital tools in the same place, providing immediate context for CAD/CAM. That is critical to enable the digital twin capabilities that many companies like ESPRIT and Autodesk have already built. Meanwhile, machining centers are adding sensors and cloud connectivity to interface more data from tool to machine, machine to CAM, and CAM to cloud. Other companies, like MachineMetrics are showing shops how to make the most of their control data without adding more sensors. Seeing beyond any one of the ways you can bring digital twin technology into your shop, it’s exciting that the entire industry is developing solutions so rapidly.
It is also critically important to notice one last thing: We have only reached this point because of a shared goal, and the entire ecosystem will need to continue to work together to bring this technology “to life.”