Digital Twin Models: Functions, Challenges, and Industry Applications

被引：4

作者：

Rayhana, Rakiba ^{[1
]}

Bai, Ling ^{[1
]}

Xiao, Gaozhi ^{[2
]}

Liao, Min ^{[3
]}

Liu, Zheng ^{[1
]}

机构：

[1] Univ British Columbia, Sch Engn, Kelowna, BC V1V 1V7, Canada

[2] Natl Res Council Canada, Adv Elect & Photon Res Ctr, Ottawa, ON K1A 0R6, Canada

[3] Natl Res Council Canada, Aerosp Res Ctr, Ottawa, ON K1A 0R6, Canada

来源：

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION | 2024年 / 8卷

关键词：

Digital twins; models; concept; types of the digital twin; functionalities; industry application; LIFE-CYCLE MANAGEMENT; OF-THE-ART; DECISION-MAKING; BAYESIAN NETWORK; FAULT-DIAGNOSIS; SENSOR DATA; BIG DATA; ARCHITECTURE; FRAMEWORK; SYSTEM;

D O I：

10.1109/JRFID.2024.3387996

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In the rapidly evolving landscape of Industry 4.0, digital twins have emerged as a transformative technology across various industrial sectors. This paper presents a comprehensive, in-depth review of digital twin models in terms of the concept and evolution, fundamental components and frameworks, and existing digital twin models based on their functionalities. The paper also discusses how the existing digital twin models are used/adopted in different industries and highlights the existing challenges and potential solutions to address the current issues. This paper aims to provide researchers and industry professionals with a clear insight into the unique benefits and applications of different digital twin models. This review will help to comprehend their significance for specific industrial purposes and foster the advancement of state-of-the-art techniques in this field.

引用

页码：282 / 321

页数：40

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