Skip to main content

Digital Twins in the Industry: Maturity, Functions, Effects

  • 550 Accesses

Part of the Lecture Notes in Information Systems and Organisation book series (LNISO,volume 54)

Abstract

A digital twin is one of the most important technological concepts within Industry 4.0. The term is often used in current research and practice on industrial transformation. The article determines the place of a digital twin, highlights its most important characteristics, the technologies used, and evaluates the possibilities of application and effects for the industry. In the author’s opinion, it is important to assess the twin maturity, which allows separating this concept from the means of industrial automation. The complexity studying this object predetermines the need to use the methodology of collecting fragmented data, systematization of scientists’ opinions, and analysis of practical experience. The author identified definitions of the digital twin concept and formulated the necessary features of a digital twin, including a virtual multidisciplinary model of the object, automatic and bi-directional data exchange, and intelligent control capabilities. Maturity criteria were proposed for classifying digital twins; the key digital technologies were distributed on a maturity scale. In terms of the use of a digital twin in industry, the author proposed the structure of the main economic effects in improving the quality of business processes, creating a product, and implementing industrial innovation. An important area of further research is to analyze the economic security of the use of digital twins and data, as well as address the problem of information overload.

Keywords

  • Digital twin
  • Industry transformation
  • Digital twin maturity

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-94617-3_1
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   139.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-94617-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   179.99
Price excludes VAT (USA)
Fig. 1
Fig. 2

References

  1. Alam, K. M., & Saddik, A. E. (2017). C2PS: A digital twin architecture reference model for the cloud-based cyber-physical systems. IEEE Access, 5, 2050–2062. https://doi.org/10.1109/ACCESS.2017.2657006

    CrossRef  Google Scholar 

  2. Bajaj, M., Cole, B., & Zwemer, D. (2016). Architecture to geometry—Integrating system models with mechanical design. In SPACE Conferences and Exposition: AIAA SPACE, Long Beach, California. https://doi.org/10.2514/6.2016-5470

  3. Borovkov, A. I., Gamzikova, A. A., Kukushkin, K. V., & Rjabov, Ju. A. (2019). Digital twins in the high-tech industry. Summary report. Politeh Press.

    Google Scholar 

  4. Borovkov, A. I., Ryabov, Yu. A., Metreveli, I. S., & Alikina, E. A. (2019). Direction technet of the national technological initiative. Innovations, 11(253), 50–72.

    Google Scholar 

  5. Erikstad, S. O. (2017). Merging physics, big data analytics, and simulation for the next-generation digital twins. In HIPER’17: 11th Symposium on High-Performance Marine Vehicles, Zevenwacht (pp. 140–150). Technical University Hamburg.

    Google Scholar 

  6. Glaessgen, E. H., & Stargel, D. S. (2012). The digital twin paradigm for future NASA and U.S. Air Force vehicles. In 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. https://doi.org/10.2514/6.2012-1818

  7. Goncharov, A. S., & Saklakov, V. M. (2018). Information and telecommunications systems and technologies. In Materials of the Supreme Scientific and Practical Conference (pp. 24–26). KGTU.

    Google Scholar 

  8. Graessler, I., & Poehler, A. (2017). Integration of a digital twin as human representation in a scheduling procedure of a cyber-physical production system. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 289–293). https://doi.org/10.1109/IEEM.2017.8289898

  9. Grand View Research. (2021). Digital twin market size, share & trends analysis report by end-use (automotive & transport, retail & consumer goods, agriculture, manufacturing, energy & utilities), by region, and segment forecasts, 2021–2028. https://www.grandviewresearch.com/industry-analysis/digital-twin-market

  10. Grieves, M., & Vickers, J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. In F. J. Kahlen, S. Flumerfelt, & A. Alves (Eds.), Transdisciplinary perspectives on complex systems. Springer. https://doi.org/10.1007/978-3-319-38756-7

  11. High Tech Software Cluster. (2018). What is the value of a digital twin? https://hightechsoftwarecluster.nl/en/technology/what-is-a-digital-twin-and-what-value-does-it-deliver/

  12. High value manufacturing catapult. (2018). Feasibility of an immersive digital twin: The definition of a digital twin and discussions around the benefit of immersion. https://www.amrc.co.uk/files/document/219/1536919984_hvm_catapult_digital_twin_dl.pdf.

  13. Hribernik, K. A., Rabe, L., Thoben, K.-D., & Schumacher, J. (2006). The product avatar as a product-instance-centric information management concept. International Journal of Product Lifecycle Management (IJPLM), 1(4). https://doi.org/10.1504/IJPLM.2006.011055

  14. Kiritsis, D., Bufardi, A., & Xirouchakis, P. (2003). Research issues on product lifecycle management and information tracking using smart embedded systems. Advanced Engineering Informatics, 17(3–4), 189–202. https://doi.org/10.1016/S1474-0346(04)00018-7

    CrossRef  Google Scholar 

  15. Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). Digital twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, 51(11), 1016–1022. https://doi.org/10.1016/j.ifacol.2018.08.474

    CrossRef  Google Scholar 

  16. Liu, M., Fang, S., Dong, H., & Xu, C. (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58, B, 346–361. https://doi.org/10.1016/j.jmsy.2020.06.017

  17. Lubell, J., Frechette, S. P., Lipman, R. R., Proctor, F. M., Horst, J. A., Carlisle, M., & Huang, P. J. (2013), Model-based enterprise summit report. National Institute of Standards and Technology, U.S. Department of Commerce. https://doi.org/10.6028/NIST.TN.1820

  18. Madni, A. M., Madni, C. C., & Lucero, S. D. (2019). Leveraging digital twin technology in model-based systems engineering. Systems, 7(1), 7. https://doi.org/10.3390/systems7010007

    CrossRef  Google Scholar 

  19. Negri, E., Fumagalli, L., & Macchi, M. (2017). A review of the roles of digital twin in CPS-based production systems. Procedia Manufacturing, 11, 939–948. https://doi.org/10.1016/j.promfg.2017.07.198

    CrossRef  Google Scholar 

  20. Prohorov, A., & Lysachev, M. (2020). Digital twin. Analysis, trends, world experience. AljansPrint.

    Google Scholar 

  21. PwC. (2018). Digital champions. https://www.pwc.ru/ru/iot/digital-champions.pdf

  22. Research and Markets. (2020). The future of the digital twins industry to 2025 in manufacturing, smart cities, automotive, healthcare and transport. https://www.prnewswire.com/news-releases/the-future-of-the-digital-twins-industry-to-2025-in-manufacturing-smart-cities-automotive-healthcare-and-transport-301028858.html.

  23. Rosen, R., Wichert, G., Lo, G., & Bettenhausen, K. D. (2015). About the importance of autonomy and digital twins for the future of manufacturing. IFAC-PapersOnLine, 48(3), 567–572. https://doi.org/10.1016/j.ifacol.2015.06.141

    CrossRef  Google Scholar 

  24. Saddik, A. E. (2018). Digital twins: The convergence of multimedia technologies. IEEE Multimedia, 25(2), 87–92. https://doi.org/10.1109/MMUL.2018.023121167

    CrossRef  Google Scholar 

  25. Sepasgozar, S. M. E. (2021). Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment. Buildings, 11, 151. https://doi.org/10.3390/buildings11040151

    CrossRef  Google Scholar 

  26. Schuh, G., & Blum, M. (2016). Design of a data structure for the order processing as a basis for data analytics methods. In Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 2164–2169). https://doi.org/10.1109/PICMET.2016.7806715

  27. Siedlak, D. J. L., Pinon, O. J., Schlais, P. R., Schmidt, T. M., & Mavris, D. N. (2018). A digital thread approach to support manufacturing-influenced conceptual aircraft design. Research in Engineering Design, 29(2), 285–308. https://doi.org/10.1007/s00163-017-0269-0

    CrossRef  Google Scholar 

  28. Singh, M., Fuenmayor, E., Hinchy, E. P., Qiao, Y., Murray, N., & Devine, D. (2021). Digital twin: Origin to future. Applied System Innovation, 4(2), 36. https://doi.org/10.3390/asi4020036

    CrossRef  Google Scholar 

  29. Stark, R., & Damerau, T. (2019). Digital twin. In S. Chatti, & T. Tolio (Eds.), CIRP encyclopedia of production engineering (pp. 1–8). Springer. https://doi.org/10.1007/978-3-642-35950-7_16870-1

  30. Trauer, J., Schweigert-Recksiek, S., Engel, C., Spreitzer, K., & Zimmermann, M. (2020). What is a digital twin? Definitions and insights from an industrial case study in technical product development. Proceedings of the Design Society: DESIGN Conference, 1, 757–766. https://doi.org/10.1017/dsd.2020.15

    CrossRef  Google Scholar 

  31. Wong, C. Y., McFarlane, D., Zaharudin, A. A., & Agarwal, V. (2002). The intelligent product-driven supply chain. Conference: Systems, Man and Cybernetics, 4. https://doi.org/10.1109/ICSMC.2002.1173319

  32. Zhuang, S., Liu, J., & Xiong, H. (2018). Digital twin-based smart production management and control framework for the complex product assembly shop-floor. International Journal of Advanced Manufacturing Technology, 96, 1149–1163.

    CrossRef  Google Scholar 

Download references

Acknowledgements

The research was carried out following the task of the Institute of Economics of the Ural Branch of the Russian Academy of Sciences.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Grigoriy Korovin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Korovin, G. (2022). Digital Twins in the Industry: Maturity, Functions, Effects. In: Kumar, V., Leng, J., Akberdina, V., Kuzmin, E. (eds) Digital Transformation in Industry . Lecture Notes in Information Systems and Organisation, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-030-94617-3_1

Download citation