Skip to main content
Springer Nature Link
Log in

A Survey of Digital Supply Chain Twins’ Implementations

  • Conference paper
  • First Online:
Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action (APMS 2022)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 663))

Abstract

This paper examines the implementations of digital twins (DTs) in the context of supply chains (SCs) and disruption risks. The concept of a digital supply chain twin (DSCT) has been a trending topic in recent years, but very little of the literature deals with case studies and actual applications. Therefore, this study concentrates on reviewing the implementations of DSCTs. Moreover, disruption risks associated with the current pandemic have encouraged the adoption of DSCTs to improve SC resilience and agility. For those reasons, this study analyzes the literature according to different industry sectors’ implementations (e.g., food, aerospace and automotive, construction, pharmaceutical, and general manufacturing industries). Additionally, literature concentrated on applications for SC risks is studied. This literature review unveils the current developments of DSCTs in the specific industries covered and risks applications. Hence, this work is intended to help SC practitioners and researchers identify challenges and potential research areas for DSCTs.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Olivares-Aguila, J., Vital-Soto, A.: Supply chain resilience roadmaps for major disruptions. Logistics 5(4), 78 (2021). https://doi.org/10.3390/logistics5040078

    Article  Google Scholar 

  2. Ivanov, D., Dolgui, A.: A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Prod. Plan. Control 32(9), 775–788 (2021). https://doi.org/10.1080/09537287.2020.1768450

    Article  Google Scholar 

  3. Cavalcante, I.M., Frazzon, E.M., Forcellini, F.A., Ivanov, D.: A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. Int. J. Inf. Manag. 49, 86–97 (2019). https://doi.org/10.1016/j.ijinfomgt.2019.03.004

    Article  Google Scholar 

  4. Digital Twin Market - Global Forecast to 2026. https://www.marketsandmarkets.com/

  5. Henrichs, E., Noack, T., Piedrahita, A.M.P., Salem, M.A., Stolz, J., Krupitzer, C.: Can a byte improve our bite? an analysis of digital twins in the food industry. Sensors 22(1), 115 (2022)

    Article  Google Scholar 

  6. Shoji, K., Schudel, S., Onwude, D., Shrivastava, C., Defraeye, T.: Mapping the postharvest life of imported fruits from packhouse to retail stores using physics-based digital twins. Res. Cons. Recycl. 176, 105914 (2022). https://doi.org/10.1016/j.resconrec.2021.105914

    Article  Google Scholar 

  7. Defraeye, T., et al.: Digital twins probe into food cooling and biochemical quality changes for reducing losses in refrigerated supply chains. Res. Cons. Recycl. 149, 778–794 (2019). https://doi.org/10.1016/j.resconrec.2019.06.002

    Article  Google Scholar 

  8. Defraeye, T., et al.: Digital twins are coming: will we need them in supply chains of fresh horticultural produce? Trends Food Sci. Technol. 109, 245–258 (2021)

    Article  Google Scholar 

  9. Tagliavini, G., Defraeye, T., Carmeliet, J.: Multiphysics modeling of convective cooling of non-spherical, multi-material fruit to unveil its quality evolution throughout the cold chain. Food Bioprod. Process. 117, 310–320 (2019). https://doi.org/10.1016/j.fbp.2019.07.013

    Article  Google Scholar 

  10. Bamunuarachchi, D., Georgakopoulos, D., Banerjee, A., Jayaraman, P.P.: Digital twins supporting efficient digital industrial transformation. Sensors 21(20), 6829 (2021)

    Article  Google Scholar 

  11. Smith, M.J.: Getting value from artificial intelligence in agriculture. Anim. Prod. Sci. 60(1), 46–54 (2019). https://doi.org/10.1071/AN18522

    Article  Google Scholar 

  12. Burgos, D., Ivanov, D.: Food retail supply chain resilience and the COVID-19 pandemic: a digital twin-based impact analysis and improvement directions. Transp. Res. Part E: Logist. Transp. Rev. 152, 102412 (2021). https://doi.org/10.1016/j.tre.2021.102412

    Article  Google Scholar 

  13. Sharma, A., Zanotti, P., Musunur, L.P.: Drive through robotics: robotic automation for last mile distribution of food and essentials during pandemics. IEEE Access 8, 127190–127219 (2020). https://doi.org/10.1109/ACCESS.2020.3007064

    Article  Google Scholar 

  14. Ho, G.T.S., Tang, Y.M., Tsang, K.Y., Tang, V., Chau, K.Y.: A blockchain-based system to enhance aircraft parts traceability and trackability for inventory management. Expert Syst. Appl. 179, 115101 (2021). https://doi.org/10.1016/j.eswa.2021.115101

    Article  Google Scholar 

  15. Mandolla, C., Petruzzelli, A.M., Percoco, G., Urbinati, A.: Building a digital twin for additive manufacturing through the exploitation of blockchain: a case analysis of the aircraft industry. Comput. Ind. 109, 134–152 (2019). https://doi.org/10.1016/j.compind.2019.04.011

    Article  Google Scholar 

  16. Lugaresi, G., Matta, A.: Automated manufacturing system discovery and digital twin generation. J. Manuf. Syst. 59, 51–66 (2021)

    Article  Google Scholar 

  17. Sharma, A., Zanotti, P., Musunur, L.P.: Enabling the electric future of mobility: robotic automation for electric vehicle battery assembly. IEEE Access 7, 170961–170991 (2019)

    Article  Google Scholar 

  18. Marmolejo-Saucedo, J.A.: Digital twin framework for large-scale optimization problems in supply chains: a case of packing problem. Mob. Netw. Appl. (2021)

    Google Scholar 

  19. Sacks, R., Brilakis, I., Pikas, E., Xie, H.S., Girolami, M.: Construction with digital twin information systems. Data-Centric Eng. 1(6) (2020). https://doi.org/10.1017/dce.2020.16

  20. Al-Saeed, Y., Edwards, D.J., Scaysbrook, S.: Automating construction manufacturing procedures using BIM digital objects (BDOs): Case study of knowledge transfer partnership project in UK. Constr. Innov. 20(3), 345–377 (2020)

    Article  Google Scholar 

  21. Lee, D., Lee, S.: Digital twin for supply chain coordination in modular construction. Appl. Sci. (Switzerland) 11(13), 5909 (2021). https://doi.org/10.3390/app11135909

    Article  Google Scholar 

  22. Greif, T., Stein, N., Flath, C.M.: Peeking into the void: digital twins for construction site logistics. Comput. Ind. 121, 103264 (2020). https://doi.org/10.1016/j.compind.2020.103264

    Article  Google Scholar 

  23. Spindler, J., Kec, T., Ley, T.: Lead-time and risk reduction assessment of a sterile drug product manufacturing line using simulation. Comput. Chem. Eng, 152, 107401 (2021). https://doi.org/10.1016/j.compchemeng.2021.107401

    Article  Google Scholar 

  24. Marmolejo-Saucedo, J.A.: Design and development of digital twins: a case study in supply chains. Mobile Netw. Appl. 25(6), 2141–2160 (2020). https://doi.org/10.1007/s11036-020-01557-9

    Article  Google Scholar 

  25. Alles, M., Gray, G.L.: “The first mile problem”: deriving an endogenous demand for auditing in blockchain-based business processes. Int. J. Account. Inf. Syst. 38, 100465 (2020). https://doi.org/10.1016/j.accinf.2020.100465

    Article  Google Scholar 

  26. Kamble, S.S., Gunasekaran, A., Parekh, H., Mani, V., Belhadi, A., Sharma, R.: Digital twin for sustainable manufacturing supply chains: current trends, future perspectives, and an implementation framework. Technol. Forecast. Soc. Change 176, 12144 (2022)

    Article  Google Scholar 

  27. Li, X., Cao, J., Liu, Z., Luo, X.: Sustainable business model based on digital twin platform network: the inspiration from Haier’s case study in China. Sustainability (Switzerland) 12(3), 1–26 (2020). https://doi.org/10.3390/su12030936

    Article  Google Scholar 

  28. Chen, Z., Huang, L.: Digital twins for information-sharing in remanufacturing supply chain: a review. Energy 220, 119712 (2021). https://doi.org/10.1016/j.energy.2020.119712

    Article  Google Scholar 

  29. Tozanli, O., Kongar, E., Gupta, S.M.: Evaluation of waste electronic product trade-in strategies in predictive twin disassembly systems in the era of blockchain. Sustainability (Switzerland) 12(13), 5416 (2020). https://doi.org/10.3390/su12135416

    Article  Google Scholar 

  30. Balderas, D., Ortiz, A., Méndez, E., Ponce, P., Molina, A.: Empowering digital twin for industry 4.0 using metaheuristic optimization algorithms: case study PCB drilling optimization. Int. J. Adv. Manuf. Technol. 113(5–6), 1295–1306 (2021). https://doi.org/10.1007/s00170-021-06649-8

    Article  Google Scholar 

  31. Martin, G., et al.: Luminaire digital design flow with multi-domain digital twins of LEDs. Energies 12(12), 2389 (2019)

    Article  Google Scholar 

  32. Frankó, A., Vida, G., Varga, P.: Reliable identification schemes for asset and production tracking in industry 4.0. Sensors (Switzerland) 20(13), 1–24 (2020). https://doi.org/10.3390/s20133709

    Article  Google Scholar 

  33. Park, K.T., Son, Y.H., Noh, S.D.: The architectural framework of a cyber physical logistics system for digital-twin-based supply chain control. Int. J. Prod. Res. 59, 1–22 (2020). https://doi.org/10.1080/00207543.2020.1788738

    Article  Google Scholar 

  34. Mazzei, D., et al.: A Blockchain Tokenizer for Industrial IOT trustless applications. Future Gener. Comput. Syst. 105, 432–445 (2020). https://doi.org/10.1016/j.future.2019.12.020

    Article  Google Scholar 

  35. Rahmanzadeh S., Pishvaee, M.S., Govindan K.: Emergence of open supply chain management: the role of open innovation in the future smart industry using digital twin network. Ann. Oper. Res. (2022). https://doi.org/10.1007/s10479-021-04254-2

  36. Dolgui, A., Ivanov, D., Sokolov, B.: Reconfigurable supply chain: the X-network. Int. J. Prod. Res. 58(13), 4138–4163 (2020). https://doi.org/10.1080/00207543.2020.1774679

    Article  Google Scholar 

  37. Ivanov, D., Dolgui, A.: Stress testing supply chains and creating viable ecosystems. Oper. Manag. Res. (2021). https://doi.org/10.1007/s12063-021-00194-z

  38. Ivanov, D., Das, A.: Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note. Int. J. Integr. Supply Manag. 13(1), 90–102 (2020). https://doi.org/10.1504/IJISM.2020.107780

    Article  Google Scholar 

  39. Ivanov, D.: Predicting the impacts of epidemic outbreaks on global supply chains: a simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transp. Res. Part E: Logist. Transp. Rev. 136, 101922 (2020). https://doi.org/10.1016/j.tre.2020.101922

    Article  Google Scholar 

  40. Nasir, S.B., Ahmed, T., Karmaker, C.L., Ali, S.M., Paul, S.K., Majumdar, A.: Supply chain viability in the context of COVID-19 pandemic in small and medium-sized enterprises: implications for sustainable development goals. J. Enterp. Inf. Manag. 35, 100–124 (2021)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Shannon School of Business, Cape Breton University, Sydney, NS, B1P 6L2, Canada

    Kristine Joy Dy, Jessica Olivares-Aguila & Alejandro Vital-Soto

Authors
  1. Kristine Joy Dy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jessica Olivares-Aguila
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alejandro Vital-Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jessica Olivares-Aguila .

Editor information

Editors and Affiliations

  1. Pohang University of Science and Technology, Pohang, Korea (Republic of)

    Duck Young Kim

  2. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Gregor von Cieminski

  3. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

Rights and permissions

Reprints and permissions

Copyright information

© 2022 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dy, K.J., Olivares-Aguila, J., Vital-Soto, A. (2022). A Survey of Digital Supply Chain Twins’ Implementations. In: Kim, D.Y., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. APMS 2022. IFIP Advances in Information and Communication Technology, vol 663. Springer, Cham. https://doi.org/10.1007/978-3-031-16407-1_59

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-16407-1_59

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16406-4

  • Online ISBN: 978-3-031-16407-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships