A digital twin modeling approach for smart manufacturing combined with the UNISON framework

被引:23
作者
Wang, Jinfeng [1 ]
Zhang, Luyao [2 ,3 ]
Lin, Kuo-Yi [4 ]
Feng, Lijie [1 ]
Zhang, Ke [5 ]
机构
[1] Shanghai Maritime Univ, China Inst FTZ Supply Chain, Shanghai 201306, Peoples R China
[2] Shanghai Maritime Univ, Sch Econ & Management, Shanghai 201306, Peoples R China
[3] Henan Univ Econ & Law, Zhengzhou 450016, Peoples R China
[4] Guilin Univ Elect Technol, Sch Business, Guilin 541004, Peoples R China
[5] Zhengzhou Univ, Sch Management Engn, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
Digital twin; UNISON framework; Five-dimensional digital twin model; New energy power battery; Smart Manufacturing; INDUSTRY; 4.0; CHALLENGES;
D O I
10.1016/j.cie.2022.108262
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the in-depth development of industry 4.0, digitalization and intellectualization have become a broad consensus, especially the digital twin. As a cutting-edge technology, the digital twin is revolutionizing the industry, but its potential is far from being tapped. Data and models, which have been proven in previous studies, are the core and foundation of the digital twin. However, most of the digital twin solutions have limitations in real settings. Previous models often neglected to provide a detailed description of the components or operational rules of the digital twin, which poses limits for practitioners. This is because there is not a completely unified understanding of the digital twin and not enough in-depth analysis of its components. This study aims to provide a methodology to construct a practical digital twin model. The method is based on the proposed five-dimensional digital twin model and the UNISON framework. To illustrate the structured procedures of this model, it was applied in an empirical study for the new energy power battery. The results have demonstrated the validity of the proposed framework. From the perspective of model construction, this study provides ideas and technical references for the application of the digital twin.
引用
收藏
页数:13
相关论文
共 48 条
  • [1] Mass Personalisation as a Service in Industry 4.0: A Resilient Response Case Study
    Aheleroff, Shohin
    Mostashiri, Naser
    Xu, Xun
    Zhong, Ray Y.
    [J]. ADVANCED ENGINEERING INFORMATICS, 2021, 50
  • [2] Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model
    Aheleroff, Shohin
    Xu, Xun
    Zhong, Ray Y.
    Lu, Yuqian
    [J]. ADVANCED ENGINEERING INFORMATICS, 2021, 47
  • [3] [Anonymous], 2011, 12 5 YEAR PLAN NATL
  • [4] Embedded Digital Twin for ARTI-Type Control of Semi-continuous Production Processes
    Borangiu, Theodor
    Oltean, Ecaterina
    Raileanu, Silviu
    Anton, Florin
    Anton, Silvia
    Iacob, Iulia
    [J]. SERVICE ORIENTED, HOLONIC AND MULTI-AGENT MANUFACTURING SYSTEMS FOR INDUSTRY OF THE FUTURE, 2020, 853 : 113 - 133
  • [5] Simulation-based decision support tool for in-house logistics: the basis for a digital twin
    Coelho, F.
    Relvas, S.
    Barbosa-Povoa, A. P.
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 153
  • [6] Decision support in productive processes through DES and ABS in the Digital Twin era: a systematic literature review
    dos Santos, Carlos Henrique
    Montevechi, Jose Arnaldo Barra
    de Queiroz, Jose Antonio
    Miranda, Rafael de Carvalho
    Leal, Fabiano
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2022, 60 (08) : 2662 - 2681
  • [7] Design and application of digital twin system for the blade-rotor test rig
    Duan, Jian-Guo
    Ma, Tian-Yu
    Zhang, Qing-Lei
    Liu, Zhen
    Qin, Ji-Yun
    [J]. JOURNAL OF INTELLIGENT MANUFACTURING, 2023, 34 (02) : 753 - 769
  • [8] Ebrahimi A, 2019, PROC IEEE INT SYMP, P1059, DOI [10.1109/ISIE.2019.8781529, 10.1109/isie.2019.8781529]
  • [9] Digital Twin: Enabling Technologies, Challenges and Open Research
    Fuller, Aidan
    Fan, Zhong
    Day, Charles
    Barlow, Chris
    [J]. IEEE ACCESS, 2020, 8 : 108952 - 108971
  • [10] Grieves M, 2016, Transdisciplinary perspectives on complex systems: new findings and approaches, P85, DOI 10.1007/978-3-319-38756-7_4