Review of digital twin about concepts, technologies, and industrial applications

计算机科学 数据科学 工程类 钥匙(锁) 系统工程 透视图(图形) 数字化转型 软件 新兴技术 万维网 人工智能 计算机安全 程序设计语言
作者
Mengnan Liu,Shuiliang Fang,Huiyue Dong,Cunzhi Xu
出处
期刊:Journal of Manufacturing Systems [Elsevier]
卷期号:58: 346-361 被引量:978
标识
DOI:10.1016/j.jmsy.2020.06.017
摘要

Various kinds of engineering software and digitalized equipment are widely applied through the lifecycle of industrial products. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on theoretical and static model has been a conventional and powerful tool for the verification, validation, and optimization of a system in its early planning stage, but no attention is paid to the simulation application during system run-time. With the development of new-generation information and digitalization technologies, more data can be collected, and it is time to find a way for the deep application of all these data. As a result, the concept of digital twin has aroused much concern and is developing rapidly. Dispute and discussions around concepts, paradigms, frameworks, applications, and technologies of digital twin are on the rise both in academic and industrial communities. After a complete search of several databases and careful selection according to the proposed criteria, 240 academic publications about digital twin are identified and classified. This paper conducts a comprehensive and in-depth review of these literatures to analyze digital twin from the perspective of concepts, technologies, and industrial applications. Research status, evolution of the concept, key enabling technologies of three aspects, and fifteen kinds of industrial applications in respective lifecycle phase are demonstrated in detail. Based on this, observations and future work recommendations for digital twin research are presented in the form of different lifecycle phases.
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