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Digital twin–based stamping system for incremental bending

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Abstract

With the rapid development of science and technology, the traditional manufacturing industry is facing huge pressure and therefore requires to make changes and to combine new technologies in the situation of the fourth industrial revolution. Digital twin, which is a virtual representation of a physical object or system across its lifecycle, using real-time data to enable understanding, learning, and reasoning, is the core technology of industry 4.0. Here in this paper, digital twin is applied in the deformation of the sheet metals based on the novel incremental bending process. First, the framework of the digital twin-based stamping system (DTSS) is illustrated, then the experimental related works, including the setup and the working principle, are presented, and last, DTSS is applied to the incremental bending process to achieve the metal plates with single curvature and variable curvature, respectively. Results show that the information on the loading path and punch speed can be obtained, and the real-time data about the punch force and the support force can be compared with the corresponding simulation results in DTSS. The proposed DTSS is proved to have good accuracy, high efficiency, and good feasibility. DTSS helps to better understand and judge the working situation of the incremental bending device, and therefore helps to make appropriate decisions on whether to make adjustments to the novel sheet metal-forming process.

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References

  1. Cinar ZM., Nuhu AA, Zeeshan Q, Korhan O (2019) Digital twins for Industry 4.0: a review. Global Joint Conference on Industrial Engineering and Its Application Areas 2019, 2-3 September 2019, Gazimagusa, Turkey

  2. Redelinghuys AJH, Basson AH, Kruger K (2019) A six-layer architecture for the digital twin: a manufacturing case study implementation. J Intell Manuf 31(6):1383–1402. https://doi.org/10.1007/s10845-019-01516-6

    Article  Google Scholar 

  3. Tao F, Liu WR, Liu JH, Liu XJ, Liu Q, Qu T, Hu TL, Zhang ZN (2018) Digital twin and its potential application exploration. Comput Integr Manuf Syst 24(1):1–18. https://doi.org/10.13196/j.cims.2018.01.001

    Article  Google Scholar 

  4. Grieves M, Vickers J (2016) Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. Transdiscipl Perspect Complex Syst:85–113

  5. Glaessgen EH, Stargel DS (2012) The digital twin paradigm for future NASA and U.S. Air Force vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, Hawaii.

  6. Grieves M (2014) Digital twin: manufacturing excellent through virtual factory replication. White paper 1:1–7

    Google Scholar 

  7. Grieves M (2005) Product lifecycle management: the new paradigm for enterprises. Int J Prod Dev 2(1/2):71–84

    Article  Google Scholar 

  8. Soderberg R, Warmefjord K, Carlson JS, Lindkvist L (2017) Toward a digital twin for real-time geometry assurance in individualized production. CIRP Ann Manuf Technol 66(1):137–140. https://doi.org/10.1016/j.cirp.2017.04.038

    Article  Google Scholar 

  9. Botkina D, Hedlind M, Olsson B, Henser J, Lundholm T (2018) Digital twin of a cutting tool. 51st CIRP Conference on Manufacturing Systems. Proc CIRP 72:215–218. https://doi.org/10.1016/j.procir.2018.03.178

    Article  Google Scholar 

  10. Zidek K, Pitel J, Adamek M, Lazorík P, Hosovsky A (2020) Digital twin of experimental smart manufacturing assembly system for Industry 4.0 concept. Sustainability 12(9). https://doi.org/10.3390/su12093658

  11. Zheng Y, Yang S, Cheng HC (2018) An application framework of digital twin and its case study. J Ambient Intell Humaniz Comput 10(3):1141–1153. https://doi.org/10.1007/s12652-018-0911-3

    Article  Google Scholar 

  12. Ma J, Chen HM, Zhang Y, Guo HF, Ren YP, Mo R, Liu LY (2020) A digital twin-driven production management system for production workshop. Int J Adv Manuf Technol 110(5-6):1385–1397. https://doi.org/10.1007/s00170-020-05977-5

    Article  Google Scholar 

  13. Kalpana K, Arunachalam N (2018) A digital twin for grinding wheel - an information sharing platform for sustainable grinding process. J Manuf Sci Eng 141(2). https://doi.org/10.1115/1.4042076

  14. Shangguan DS, Chen LP, Ding JW (2020) A digital twin-based approach for the fault diagnosis and health monitoring of a complex satellite system. Symmetry 12(8):1307. https://doi.org/10.3390/sym12081307

    Article  Google Scholar 

  15. Luo WC, Hu TL, Ye YX, Zhang CR, Wei YL (2020) A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin. Robot Comput Integr Manuf 65. https://doi.org/10.1016/j.rcim.2020.101974

  16. Xie FC, Zhou ZY (2019) Discussion on the application of digital twins in the wear of parts. Proceedings of the 9th International Conference on Computer Engineering and Networks. Adv Intellig Syst Comput 1143:145–153. https://doi.org/10.1007/978-981-15-3753-0_15

    Article  Google Scholar 

  17. Liang B, Liu W, Liu K, Zhou MD, Zhang Y, Jia ZY (2020) A displacement field perception method for component digital twin in aircraft assembly. Sensors 20(18). https://doi.org/10.3390/s20185161

  18. Grigor A, Dario C, Giuliana C (2020) Development of the simulation model for Digital Twin applications in historical masonry buildings: the integration between numerical and experimental reality. Comput Struct 238:106282. https://doi.org/10.1016/j.compstruc.2020.106282

    Article  Google Scholar 

  19. Gaikwad A, Yavari R, Montazeri M, Cole K, Bian L, Rao P (2020) Toward the digital twin of additive manufacturing – integrating thermal simulations, sensing, and analytics to detect process faults. IISE Transac 52(11):1204–1207. https://doi.org/10.1080/24725854.2019.1701753

    Article  Google Scholar 

  20. DebRoy T, Zhang W, Turner J, Babu SS (2016) Building digital twins of 3D printing machines. Scr Mater 135:119–124. https://doi.org/10.1016/j.scriptamat.2016.12.005

    Article  Google Scholar 

  21. Uriarte L, Zatarain M, Axinte D, Yagüe-Fabra J, Ihlenfeldt S, Eguia J, Olarra A (2013) Machine tools for large parts. CIRP Ann Manuf Technol 62(2):731–750. https://doi.org/10.1016/j.crip.2013.05.009

    Article  Google Scholar 

  22. Xu D, Liasi E, Guo WZ, Du RX (2005) Visual comparison of multiple tonnage signature by using snake skeleton graph. Mechan Syst Singnal Proc 19:311–328. https://doi.org/10.1016/S0888-3270(03)00098-0

    Article  Google Scholar 

  23. Du RX, Guo WZ, Xu D, Liasi E (2003) Snake skeleton graph: a new method for analyzing signals that contain spatial information. Trans ASME 125:294–302. https://doi.org/10.1115/1.1590683

    Article  Google Scholar 

  24. Dang XB, He K, Zhang FF, Zuo QY, Du RX (2019) Multi-stage incremental bending to form doubly curved metal plates based on bending limit diagram. Int J Mech Sci 155:19–30

    Article  Google Scholar 

  25. Zuo QY, He K, Dang XB, Feng W, Du RX (2017) A novel incremental sheet bending process of complex curved steel plate. J Manuf Sci Eng 139(11):111005. https://doi.org/10.1115/1.4037428

    Article  Google Scholar 

  26. Zhang FF, He K, Dang XB, Du RX (2018) Experimental and numerical study on one flexible incremental bending process. Int J Adv Manuf Technol 96(5-8):2643–2655. https://doi.org/10.1007/s00170-018-1777-4

    Article  Google Scholar 

  27. Zhang FF, Zhang J, Zuo QY, Dang XB, He K (2019) Experimental and numerical study on deformation behavior of doubly curved metal plates during incremental bending process. Int J Adv Manuf Technol 104:2739–2750. https://doi.org/10.1007/s00170-019-04144-9

    Article  Google Scholar 

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Funding

The research is supported by SIAT-CUHK Joint Laboratory of Precision Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences and SIAT Innovation Program for Excellent Young Researchers (2019Y9G031).

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Authors and Affiliations

  1. South China University of Technology, Shien-Ming Wu School of Intelligent Engineering, Guangzhou, China

    Chenghui Zhou, Bo Wei, Yangjun Lin & Ruxu Du

  2. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Feifei Zhang & Kai He

  3. Shenzhen Key Laboratory of Precision Engineering, Shenzhen, China

    Feifei Zhang & Kai He

Authors
  1. Chenghui Zhou
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  2. Feifei Zhang
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  3. Bo Wei
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  4. Yangjun Lin
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  5. Kai He
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  6. Ruxu Du
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Contributions

Chenghui Zhou wrote the paper and studied the frameworks of digital twin and carried out the experiments; Feifei Zhang helped with the framework of the paper and gave some data analysis and revision suggestions; Bo Wei helped with the experiments; Yangjun Lin helped with data processing; Kai He provided the experimental condition; Ruxu Du contributed to the main idea of digital twin applied for incremental bending process.

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Correspondence to Feifei Zhang.

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Cite this article

Zhou, C., Zhang, F., Wei, B. et al. Digital twin–based stamping system for incremental bending. Int J Adv Manuf Technol 116, 389–401 (2021). https://doi.org/10.1007/s00170-021-07422-7

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  • DOI: https://doi.org/10.1007/s00170-021-07422-7

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