Abstract

While digital twin (DT) has made significant strides in recent years, much work remains to be done in the research community and in the industry to fully realize the benefits of DT. A group of 25 industry professionals, US federal government researchers, and academics came together from 11 different institutions and organizations to identify 14 key thrusts and 3 cross-cutting areas for further DT research and development (R&D). This article presents our vision for the future of DT R&D, provides historical context for DT’s birth and growth as a field, provides examples of DTs in use in industry and the lab, and discusses the current state of DT research. We hope that this article serves as a nucleation point for future R&D efforts and provides the community with shared vision and trajectory to collectively advance DT so that society can more rapidly see the benefits of DT.

Issue Section:
Review Article
Keywords:
artificial intelligence, big data and analytics, computational foundations for engineering optimization, cyber physical system design and operation, data-driven engineering, digital twin, engineering informatics, industrial Internet of things, information management, machine learning for engineering applications, model-based systems engineering, multiscale modeling and simulation, physics-based simulations, qualification, verification and validation of computational models, virtual and augmented reality environments, virtual prototyping
Topics:
Digital twin, Modeling, Simulation

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