- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | JIANG Haifan, DING Guofu, XIAO Tong, FAN Mengjie, FU Jianlin, ZHANG Jian. Digital Twin Evolution Model and Its Applications in Intelligent Manufacturing[J]. Journal of Southwest Jiaotong University, 2022, 57(6): 1386-1394. doi: 10.3969/j.issn.0258-2724.20210202
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As a key enabling technology for the cyber-physical fusion of intelligent manufacturing, the digital twin has drawn extensive concern. And how to build a digital twin model has become a current research hotspot. At present, digital twin models are mostly focused on conceptual abstraction or specific engineering applications, and seldom consider how to construct and apply digital twin models step by step from the perspective of construction methods and processes. Therefore, this paper proposed the digital twin evolution model (DTEM), which divides the construction and application process of the digital twin into three evolution stages, namely digital model, digital shadow, and digital twin. Then, the application methods, key technologies and tool platforms of each evolution stage were discussed. And the typical applications of DTEM were explored, including intelligent equipment, intelligent production, and intelligent operation and maintenance. The applications show that the proposed model provides a feasible technical route and useful application reference for the step-by-step implementation of digital twins in intelligent manufacturing.
| [1] |
TAO F, ZHANG M. Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing[J]. IEEE Access, 2017, 5: 20418-20427. doi: 10.1109/ACCESS.2017.2756069
|
| [2] |
DING K, CHAN F T S, ZHANG X D, et al. Defining a digital twin-based cyber-physical production system for autonomous manufacturing in smart shop floors[J]. International Journal of Production Research, 2019, 57(20): 6315-6334. doi: 10.1080/00207543.2019.1566661
|
| [3] |
TAO F, ZHANG M, LIU Y S, et al. Digital twin driven prognostics and health management for complex equipment[J]. CIRP Annals, 2018, 67(1): 169-172. doi: 10.1016/j.cirp.2018.04.055
|
| [4] |
陶飞,刘蔚然,张萌,等. 数字孪生五维模型及十大领域应用[J]. 计算机集成制造系统,2019,25(1): 1-18.
TAO Fei, LIU Weiran, ZHANG Meng, et al. Five-dimension digital twin model and its ten applications[J]. Computer Integrated Manufacturing Systems, 2019, 25(1): 1-18.
|
| [5] |
BAO J S, GUO D S, LI J, et al. The modelling and operations for the digital twin in the context of manufacturing[J]. Enterprise Information Systems, 2019, 13(4): 534-556. doi: 10.1080/17517575.2018.1526324
|
| [6] |
CECIL J, ALBUHAMOOD S, CECIL-XAVIER A, et al. An advanced cyber physical framework for micro devices assembly[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(1): 92-106. doi: 10.1109/TSMC.2017.2733542
|
| [7] |
JIANG H F, QIN S F, FU J L, et al. How to model and implement connections between physical and virtual models for digital twin application[J]. Journal of Manufacturing Systems, 2021, 58: 36-51. doi: 10.1016/j.jmsy.2020.05.012
|
| [8] |
KRITZINGER W, KARNER M, TRAAR G, et al. Digital twin in manufacturing: a categorical literature review and classification[J]. IFAC-PapersOnLine, 2018, 51(11): 1016-1022. doi: 10.1016/j.ifacol.2018.08.474
|
| [9] |
江海凡,丁国富,张剑. 数字孪生车间演化机理及运行机制[J]. 中国机械工程,2020,31(7): 824-832, 841. doi: 10.3969/j.issn.1004-132X.2020.07.008
JIANG Haifan, DING Guofu, ZHANG Jian. Evolution and operation mechanism of digital twin shopfloors[J]. China Mechanical Engineering, 2020, 31(7): 824-832, 841. doi: 10.3969/j.issn.1004-132X.2020.07.008
|
| [10] |
QI Q L, TAO F, ZUO Y, et al. Digital twin service towards smart manufacturing[J]. Procedia CIRP, 2018, 72: 237-242. doi: 10.1016/j.procir.2018.03.103
|
| [11] |
赵颖,侯俊杰,于成龙,等. 面向生产管控的工业大数据研究及应用[J]. 计算机科学,2019,46(增1): 45-51.
ZHAO Ying, HOU Junjie, YU Chenglong, et al. Study and application of industrial big data in production management and control[J]. Computer Science, 2019, 46(S1): 45-51.
|
| [12] |
陈建. 通用五轴数控加工仿真系统研发[D]. 成都: 西南交通大学, 2014.
|
| [13] |
肖通,江海凡,丁国富,等. 五轴磨床数字孪生建模与监控研究[J]. 系统仿真学报,2021,33(12): 2880-2890.
XIAO Tong, JIANG Haifan, DING Guofu, et al. Research on digital twin-based modeling and monitoring of five-axis grinder[J]. Journal of System Simulation, 2021, 33(12): 2880-2890.
|
| [14] |
骆伟超. 基于Digital Twin的数控机床预测性维护关键技术研究[D]. 济南: 山东大学, 2020.
|
| [15] |
丁国富, 江海凡, 罗樟圳, 等. 一种任务车间生产计划验证方法: CN110989527A[P]. 2020-04-10.
|
| [16] |
罗樟圳,江海凡,付建林,等. 基于组合赋权的离散车间生产计划综合评价[J]. 系统仿真学报,2021,33(8): 1856-1865.
LUO Zhangzhen, JIANG Haifan, FU Jianlin, et al. Combination weighting-based comprehensive evaluation for discrete workshop production plan[J]. Journal of System Simulation, 2021, 33(8): 1856-1865.
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