The emergence of the metaverse and Web 3.0 is adding to the possibilities around augmented and virtual reality (AR/VR), simulation, and digital twin technologies. But it's also creating some confusion. While some of this is years away, simulation and digital twin technologies are being implemented now. Dan Riley, analytics manager at Interstates, connected with Automation World on this topic.
First, Riley explained digital twins and how they can be applied to devices, machines, and the entire production. "A digital twin is a digital representation of a physical object or process," Riley said. "At its most basic level, a digital twin is a comprehensive operational dashboard [of the device, machine, or factory it is representing]."
Digital twin technology can show real-time operating conditions and is excellent in research and development as well as testing and commissioning.
Level of difficulty
So, what is the difficulty of implementing digital twin technology for a typical manufacturer?
"First, you're going to need to have a basic understanding of the digital twin technology you're using before you can really begin—and that means you need to have a solid plant network supporting all the assets you want to have digitized," Riley said. He mentioned a few specifics.
- Clean, mature model of your data
- Write capabilities from the digital twin back to the PLC
- Access in the network and platform with write permissions
These initial steps mean that digital twin technology is not for entry-level digitization, said Riley. He added that, depending on the complexity of your digital twin implementation, you'd want to have a reliable plant Wi-Fi network to access the digital twin hands-free.
Riley expects added AR/VR capabilities to remain with larger manufacturers, but digital twin dashboard technology is possible for mid-tier manufacturers.
There are, of course, cost considerations, and they vary depending on what vendor you're working with and how extensive your use of the digital twin will be.
Riley shares that it's important to recognize two costs associated with digital twin technology—platform and capabilities with the digital twin. By first investing in your data and understanding it across operations, you can save on digital twin technology.
This article was originally published on Automation World.