Skip to main content

A Digital Twin Generic Architecture for Data-Driven Cyber-Physical Production Systems

  • Conference paper
  • First Online:
Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2022)

Abstract

The integration of digital technology within organizations into their products, services, production, corresponding to various domains, which was started in the context of the Industry 4.0 initiative, has imposed the appearance of new emergent concepts and technologies. One of these is Digital Twin, which represents a virtual model of a physical object, which dynamically pairs the physical entity with its digital replica. The virtual system is connected to the real world through data transmission channels to acquire, analyse, process and simulate data within a virtual model. Thus, a Digital Twin improves the performance of the real entity; such systems are increasingly used today in various fields of activity. The progress realized in computation and communication enables digital representations of physical systems. This work proposes a generic Digital Twin architecture, together with main design guidelines and integrated technologies such as IoT, intended to be used in Cyber-Physical Production Systems for experimental applications. The proposed Digital Twin architecture offers the possibility to be accessed by a remote connection or locally. Several Digital Twin types, layers and applications, in the Data-Driven Cyber-Physical Production Systems context, are presented in the paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Marr, B.: What is Digital Twin Technology and Why Is It so Important? Forbes (2017). https://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital-twin-technology-and-why-is-it-so-important/

  2. Glaessgen, E.H., Stargel, D.S.: The digital twin paradigm for future NASA and U.S. Air force vehicles. Collect. Tech. Pap. - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, pp. 1–14 (2012)

    Google Scholar 

  3. Fei, T., Weiran, L., Meng, Z., et al.: Five-dimension digital twin model and its ten applications. Comput. Integr. Manuf. Syst. 25(1), 1–18 (2019)

    Google Scholar 

  4. Negri, E., Fumagalli, L., Macchi, M.: A review of roles of digital twin in CPS-based production systems. Procedia Manufact. 11, 939–948 (2017). Digital_Twin_Architecure_2_ICCE_08662081_Artigo

    Google Scholar 

  5. Liu, Y., Peng, Y., Wang, B., Yao, S., Liu, Z.: Review on cyber-physical systems. IEEE/CAA J. Automatica Sinica 4(1), 27–40 (2017)

    Article  Google Scholar 

  6. Singh, M., et al.: Digital twin: origin to future. Appl. Syst. Innov. 4, 36 (2021)

    Article  Google Scholar 

  7. Dahmen, U., Rossmann, J.: Experimentable digital twins for a modeling and simulation-based engineering approach. In: Proceedings of the 2018 IEEE International Systems Engineering Symposium (ISSE), Rome, Italy, pp. 1–3 (2018)

    Google Scholar 

  8. Boschert, S., Rosen, R.: Digital twin - the simulation aspect. In: Hehenberger, P., Bradley, D. (eds.) Mechatronic Futures, pp. 59–74. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32156-1_5

    Chapter  Google Scholar 

  9. Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., Calinescu, A.: Digital Twins: State of the Art Theory and Practice, Challenges and Open Research Questions, arXiv:2011.02833 (2021)

    Google Scholar 

  10. Juarez, M., Botti, V., Giret, A.: Digital twins: review and challenges. J. Comput. Inf. Sci. Eng. 21, 030802 (2021)

    Article  Google Scholar 

  11. Sidyuk, A.: Five Examples of Digital Twin Technology in Different Industries (Use Cases and Benefits) (2021). https://www.softeq.com/blog/5-digital-twin-examples-in-different-industries

  12. Autiosalo, J., Vepsalainen, J., Viitala, R., Tammi, K.: A feature-based framework for structuring industrial digital twins. IEEE Access 8, 1193–1208 (2019)

    Article  Google Scholar 

  13. Lim, K., Zheng, P., Chen, C.: A state-of-the-art survey of digital twin: techniques, engineering product lifecycle management and business innovation perspectives. J. Intell. Manuf. 31, 1313–1337 (2020)

    Article  Google Scholar 

  14. Ran, Y., Lin, P., Zhou, X., Wen, Y.: A survey of predictive maintenance: systems, purposes and approaches. Comput. Sci. Eng. (2019). http://xxx.lanl.gov/abs/1912.07383. Accessed 9 July 2021

  15. Sharma, M., George, J.P.: Digital Twin in the Automotive Industry: Driving Physical-Digital Convergence, White Paper; Tata Consultancy Services Ltd., Mumbai, India (2018)

    Google Scholar 

  16. Rathore, M., Shah, S., Shukla, D., Bentafat, E., Bakiras, S.: The role of AI, machine learning, and big data in digital twinning: a systematic literature review, challenges, and opportunities. IEEE Access 9, 32030–32052 (2021)

    Article  Google Scholar 

  17. Quirk, D., Lanni, J., Chauhan, N.: Digital twins: answering the hard questions. ASHRAE J. 62, 22–25 (2020)

    Google Scholar 

  18. Qi, Q., et al.: Enabling technologies and tools for digital twin. J. Manuf. Syst. 53, 3–21 (2021)

    Article  Google Scholar 

  19. Zhou, M., Yan, J., Feng, D.: Digital twin framework and its application to power grid online analysis. CSSE J. Power Energy Syst. 5, 391–398 (2019)

    Google Scholar 

  20. Shengli, W.: Is Human Digital Twin possible? Computer Methods Programs Biomed. Update 2021, vol. 1, p. 100014 (2021)

    Google Scholar 

  21. Barricelli, B., Casiraghi, E., Gliozzo, J., Petrini, A., Valtolina, S.: Human digital twin for fitness management. IEEE Access 8, 26637–26664 (2020). https://doi.org/10.1109/ACCESS.2020.2971576

    Article  Google Scholar 

  22. Laubenbacher, R., et al.: Using digital twins in viral infection. Science 371, 1105–1106 (2021)

    Article  Google Scholar 

  23. Laamarti, F., Badawi, H., Ding, Y., Arafsha, F., Hafidh, B., El Saddik, A.: An ISO/IEEE 11073 standardized digital twin framework for health and well-being in smart cities. IEEE Access 8, 105950–105961 (2020)

    Article  Google Scholar 

  24. Malakuti, S., Grüner, S.: Architectural aspects of digital twins in IIoT systems. In: Proceedings of 12th European Conference on Software Architecture Companion, ECSA 2018, pp. 1–2 (2018)

    Google Scholar 

  25. OPC Foundation: OPC UA Part 1 – Overview and Concepts 1.03 Specification (2015)

    Google Scholar 

  26. Haskamp, H., Orth, F., Wermann, J., Colombo, A., W.: Implementing an OPC UA interface for legacy PLC-based automation systems using the Azure cloud: an ICPS-architecture with a retrofitted RFID system, pp. 115–121. IEEE Industrial Cyber-Physical Systems (ICPS), St. Petersburg (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eugen Pop .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Iliuţă, M., Pop, E., Caramihai, S.I., Moisescu, M.A. (2023). A Digital Twin Generic Architecture for Data-Driven Cyber-Physical Production Systems. In: Borangiu, T., Trentesaux, D., Leitão, P. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2022. Studies in Computational Intelligence, vol 1083. Springer, Cham. https://doi.org/10.1007/978-3-031-24291-5_6

Download citation

Publish with us

Policies and ethics