Research on Digital Twin System of Intelligent Workshop and Application of Historical Data

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Advanced Manufacturing and Automation XI (IWAMA 2021)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 880))

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Abstract

Digital twin technology has attracted much attention in the manufacturing industry in recent years. It can provide practical functions such as real-time monitoring, status parameter monitoring, fault diagnosis, fault prediction, and offline debugging. With the development of information technology, more and more data are collected in manufacturing, and these data have great application value. However, in the current research, the integration of the digital twin system and historical data is not close. This article combines historical data with the digital twin system. It introduces the application of historical data in the digital twin system by reproducing historical scenes as an example, which has specific application value. This article first introduces the basic framework of the digital twin system, then introduces the method of historical accessing data in the digital twin system, and also proposes some application scenarios of historical data in the digital twin system, and finally puts forward the development direction of the digital twin system Some opinions.

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References

  1. Schioenning, L., Maria, S., Lassen, A.H.: Design parameters for smart manufacturing innovation processes. Procedia CIRP 93, 365–370 (2020)

    Article  Google Scholar 

  2. Tao, F., et al.: Digital twin and its potential application exploration. Comput. Integr. Manuf. Syst. 24(1), 1–18 (2018)

    Google Scholar 

  3. Guo, L., et al.: Data collection and transmission method for workshop production in intelligent manufacturing terminal. Mach. Electron. 37(8), 21–24 (2019)

    Google Scholar 

  4. Yang, J., et al.: Integrated platform and digital twin application for global automotive part suppliers. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds.) APMS 2020. IAICT, vol. 592, pp. 230–237. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-57997-5_27

    Chapter  Google Scholar 

  5. Miao, Q., Zou, W., Liu, L., Wan, X., Wu, P.: Intelligent workshop digital twin virtual reality fusion and application. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds.) IWAMA 2019. LNEE, vol. 634, pp. 585–592. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-2341-0_73

    Chapter  Google Scholar 

  6. Grieves, M., Vickers, J.: Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Kahlen, F.-J., Flumerfelt, S., Alves, A. (eds.) Transdisciplinary Perspectives on Complex Systems, pp. 85–113. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-38756-7_4

    Chapter  Google Scholar 

  7. Di Marino, S., Fiadone, L., Peron, A., Vitale, V.N., Riccabone, A.: Industrial internet of things: persistence for time series with NoSQL databases. In: Proceedings – 2019 IEEE 28th Internetional Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, pp. 340–345 (2019)

    Google Scholar 

Download references

Acknowledgment

The support of Shanghai University and Huayu Intelligent Equipment Technology Co., Ltd for author’s research is greatly appreciated. The work described in this article has been conducted as part of the research project Development and Application of Key Technologies for Car Intelligent Chassis Assembly Line (No. 19511105200), which is supported by Shanghai Science and Technology Committee of China.

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Correspondence to Muchen Yang .

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Yang, M., Liu, L., Gao, Z., Wei, W. (2022). Research on Digital Twin System of Intelligent Workshop and Application of Historical Data. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation XI. IWAMA 2021. Lecture Notes in Electrical Engineering, vol 880. Springer, Singapore. https://doi.org/10.1007/978-981-19-0572-8_3

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