Physics-based CAE simulation models (FEA, CFD, Multibody Dynamics, Electromagnetics) have become realistic enough, and execute fast enough, to prove their mainstream business value during the design, development and manufacturing phases of the Product Performance Lifecycle (PPL). Now they are moving beyond those phases into the entire life cycle of products and systems by being able to be updated/modified to reflect the ongoing true in-field status/condition of such products and by being subject to the actual in-field loading and boundary conditions obtained from arrays of networked sensors (a part of the Industrial Internet of Things – IIoT movement). The resulting updated models and sensor-driven physical actions now constitute what are called Digital Twins. Such Twins can then be used to anticipate and schedule needed maintenance and accurately predict the behavior of future proposed operational modifications and/or design changes (i.e., repairs or retrofits) to the actual physical structures and systems that they represent in digital form.
As is true with any emerging field of technology, the Digital Twins topic is just now coalescing into a clearer definition of what it actually means in practice. Many market observers and vendors have offered up their views on what Digital Twins means to them (please dig deeper by clicking on the various items on the “How It Works” Digital Twins/IIoT pull-down tab here on the Revolution in Simulation™ website for more details on these understandings and evolving meanings of Digital Twins).
The components and ingredients necessary for useful CAE-based Digital Twins have been around in some form for a while, but their synergistic combination is just now beginning to bear initial business fruit. Key enablers are the ever increasing physical accuracy and execution speed of CAE models, the declining costs of high-performance computing (HPC), expanding cloud HPC accessibility, and low-cost sensors. As these Digital Twin-based workflows throughout the PPL become more prevalent, the result is that many more CAE simulations will be built into those workflows and executed more and more frequently and routinely (even in a more automated way). The automation of such workflows will democratize simulation (=number of simulations being routinely executed) without necessarily requiring a great increase in trained CAE engineering talent to run them. Such talent will spend more value-added productive time in creating and automating the Digital-Twin-based workflows.
Dennis Nagy, Digital Twins/IIoT Area Moderator