Digital twin modeling technology and intelligent application of CNC machine tool

被引：0

作者：

Sun X. ^{[1
]}

Zhang F. ^{[1
]}

Zhou Z.F. ^{[1
]}

Wang J. ^{[1
]}

Huang Z. ^{[2
]}

Xue R. ^{[2
]}

机构：

[1] School of Mechanical and Transportation Engineering, China University of Petroleum, Beijing

[2] GENERTEC Machine Tool Engineering Research Institute Co.Ltd.,, Beijing

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 03期

基金：

中国国家自然科学基金;

关键词：

CNC machine tool; digital twin; intelligent application; multi-domain modeling;

D O I：

10.13196/j.cims.2023.IM01

中图分类号：

学科分类号：

摘要：

As a basic equipment for manufacturing, CNC machine tools are developing towards high speed, high precision, high flexibility and high intelligence. For the intelligent needs of virtual commissioning, health management and performance evaluation of CNC machine tools in intelligent manufacturing, a digital twin implementation framework of CNC machine tools for intelligent applications was established, a digital twin multi-domain modeling process based on geometric, physical and data models was proposed, and the key enabling technologies in the construction of digital twin models was studied. A multi-layer hierarchical CNC machine tool digital twin function implementation framework was built to promote the implementation of digital twin intelligent applications of CNC machine tools. It also develops A digital twin CNC machine tool application system based on the industrial internet architecture was developed, a CNC machine tool twin model in virtual space was constructed using data information in physical space, and the performance evaluation, health management, virtual debugging and other intelligent application service modules was established to realize intelligent applications of digital twin CNC machine tools and improve the intelligence level of CNC machine tools. © 2024 CIMS. All rights reserved.

引用

页码：825 / 836

页数：11

共 27 条

[1]

LENG J, WANG D, SHEN W, Et al., Digital twins-based smart manufacturing system design in Industry 4. 0: A review [ J ], Journal of Manufacturing Systems, 60, pp. 119-137, (2021)

[2]

Shigen GAO, ZHOU Min, ZHENG Wei, Et al., Intelligent operation and maintenance for advanced equipment based on digital twin: Challenges and future [ J ], Computer Integrated Manufacturing Systems, 2 8, 7, pp. 1953-1965, (2022)

[3]

SCHLUSE M, PRIGGEMEYER M, ATORF L, Et al., Experimentable digital twins-Streamlining simulation-based systems engineering for industry 4. 0, IEEE Transactions on Industrial Informatics, 14, 4, pp. 1722-1731, (2018)

[4]

ZHUANG C, LIU J, XIONG H., Digital twin-based smart production management and control framework for the complex product assembly shop-floor, The International Journal of Advanced Manufacturing Technology, 96, 1, pp. 1149-1163, (2018)

[5]

LIU C, JIANG P, JIANG W L., Web-based digital twin modeling and remote control of cyber-physical production systems [ J ], Robotics and Computer-Integrated Manufacturing, 64, (2020)

[6]

YANG X, RAN Y, ZHANG G, Et al., A digital twin-driven hybrid approach for the prediction of performance degradation in transmission unit of CNC machine t o o l [ J ], Robotics and Computer-Integrated Manufacturing, 73, (2022)

[7]

WEI Yixiong, GUO Lei, CHEN Liangxi, Et al., Research and implementation of digital twin workshop based on real-time data driven, Computer Integrated Manufacturing Systems, 27, 2, pp. 352-363, (2021)

[8]

WEI Y, HU T, ZHOU T, Et al., Consistency retention method for CNC machine tool digital twin model[J], Journal of Manufacturing Systems, 58, pp. 313-322, (2020)

[9]

SCAGLIONI B, FERRETTI G., Towards digital twins through object-oriented modelling: A machine tool case study, IFACPapersOnLine, 51, 2, pp. 613-618, (2018)

[10]

VISHNU V S, VARGHESE K G, GURUMOORTHY B., A data-driven digital twin of CNC machining processes for predicting surface roughness [J ], Procedia CIRP, 104, pp. 1065-1070, (2021)

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