A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts-Reference-Cited by-同舟云学术

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A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts

Published:2022-12-19 Issue:7-8 Volume:124 Page:2847-2861
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Zhang Chao,Zhou Guanghui,Xu Qingfeng,Wei Zhibo,Han Chong,Wang Zenghui

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Key Research and Development Projects of Shaanxi Province

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-022-10667-5.pdf

Reference29 articles.

1. Zhao X, Zheng L, Wang Y et al (2022) Services-oriented intelligent milling for thin-walled parts based on time-varying information model of machining system. Int J Mech Sci 219:107125. https://doi.org/10.1016/j.ijmecsci.2022.107125

2. Li W, Wang L, Yu G (2022) Chatter prediction in flank milling of thin-walled parts considering force-induced deformation. Mech Syst Signal Pr 165:108314. https://doi.org/10.1016/j.ymssp.2021.108314

3. Glaessgen EH, Stargel DS (2012) The digital twin paradigm for future NASA and U.S. Air force vehicles. Proceedings of the IAA/ASME/ASCE/AHS/ASC Structures. Struct Dynamics Mater Conference. https://doi.org/10.2514/6.2012-1818

4. Pan L, Guo X, Luan Y et al (2021) Design and realization of cutting simulation function of digital twin system of CNC machine tool. Procedia Computer Science 183:261–266. https://doi.org/10.1016/j.procs.2021.02.057

5. Liu K, Song L, Han W et al (2022) Time-varying error prediction and compensation for movement axis of CNC machine tool based on digital twin. IEEE T Ind Inform 18:109–118. https://doi.org/10.1109/tii.2021.3073649

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