What Is a Digital Twin?

One of the first industries to consider the use of digital twins is the aerospace industry. In a very insightful paper, Glaessgen and Stargel explain the use of digital twins for vehicle certification and fleet management. The digital twin for a vehicle would be used to “continuously forecast the health of the vehicle or system, the remaining useful life, and the probability of mission success.” The description of the digital twin is the following: “A digital twin is an integrated multiphysics, multiscale, probabilistic simulation of an as-built vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin.”

The term “digital twin” was coined by Michael Grieves at the University of Michigan in 2011.  The concept had already been formulated by Grieves in 2002, but was then referred to as a “mirrored spaces model.” In Grieves’s definition, the digital twin concept consists of a real space and a virtual space. The virtual space contains all of the information gathered from the real space. It also contains a high-fidelity description of the physical device or process from the microscopic level to the geometric, macroscopic level. The description provided by the digital twin should be “virtually indistinguishable from its physical counterpart.”

ANSYS Twin Builder enables equipment operators to create a virtual representation – a digital twin – of machines that helps monitor performance and maintenance requirements, improving the machine’s sustainability and efficiency. At ANSYS 2019 R1, ANSYS Twin Builder supports digital twin runtime generation capabilities and model export for industrial internet of things platforms. The update empowers users to unlock actionable insights from field asset data through the use of physics and simulation-based analytics.