Hybrid systems offer digital twins that are both quick and exact

Nov. 25, 2020
Digital twins based on data analytics require immense amounts of data for accuracy, and, while physics-based simulation models are highly accurate, they take an incredible amount of time to run.

The current digital twin market is estimated at about $4 billion annually, and, by 2025, it is expected to expand to $26 billion, said Prith Banerjee, chief technology officer at Ansys. He discussed the challenges and opportunities in this expanding market during his Digital Strategists keynote presentation at this week’s Automation Fair At Home event, presented by Rockwell Automation.

Digital twins based on data analytics require immense amounts of data for accuracy, and, while physics-based simulation models are highly accurate, they take an incredible amount of time to run. New hybrid systems are combining the best of both worlds, for a digital twin that is both quick and exact.

“Many confuse digital twins with a model of a physical asset,” Banerjee said. A digital twin must have three primary elements: a physical asset; a model of the physical asset in a virtual space; and a link for data to flow from the real space to the virtual.

To learn more, read "Hybrid twins yield quick and accurate results" from Control.

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