Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges

Weifei Hu,Zhenyu Liu,Xiaoyu Deng,Tongzhou Zhang,Jianrong Tan

doi:10.1108/jimse-12-2020-010

Weifei Hu, Zhenyu Liu + Show 3 more

Open Access

https://doi.org/10.1108/jimse-12-2020-010

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Abstract

Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.

Highlights

To trigger the core value of the Internet of things (IoT), stakeholders in both industry and academia are merging a large number of physical entities with virtual models, which is considered one of the most important aspects of the digital twin (DT)
In accordance with the development and application of a cyber-physical system (CPS), DT has become a key component in the Made in China 2025 plan, which targets the development of intelligent control systems; industrial application software, fault diagnosis software and related tools; and sensor and communication system protocols to realize real-time connection, accurate identification, effective interaction, and intelligent control of manufacturing equipment and products (State Council Of China, 2015)
The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area

Summary

Introduction

To trigger the core value of the Internet of things (IoT), stakeholders in both industry and academia are merging a large number of physical entities with virtual models, which is considered one of the most important aspects of the digital twin (DT). The review categorizes the various DT applications from two perspectives (1) applications in four product-lifecycle phases (i.e. product design, manufacturing, operation and maintenance and recycling) and (2) applications in four engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering, and IoT applications Another contribution of this paper is that environmental coupling technologies are highlighted and summarized for creating highfidelity virtual components in DT. The concept of DT was proposed by Michael Grieves as the “virtual digital representation equivalent to physical products” in 2003 (Grieves, 2014), the development of DT was stagnant until 2012, when NASA defined DT as an integrated multi-physics, multi-scale, probabilistic simulation of an as-built vehicle or system that employs the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin (Glaessgen and Stargel, 2012). Existing DT definitions may highlight specific aspects or components of DT systems, a general definition of DT may refer to the digital replica of physical assets, processes, people, places and systems, which provides both the elements and the dynamics of how the complex system operates and evolves throughout its lifecycle

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