Skip to main content
SpringerLink
Log in

A digital twin framework for large comprehensive ports and a case study of Qingdao Port

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The increase in port scale and business complexity has led to an increased demand for comprehensive and lean control on ports. The current operation mode is facing the bottleneck of the increasingly significant production efficiency and performance. Digital twin (DT) technology realizes holographic visual management and control patterns using cyber-physical fusion and promotes the transformation of a port to an intelligent operation mode. In this paper, the framework of a digital twin application system is proposed based on the analysis of business characteristics of large-scale comprehensive ports. Construction methods and technologies such as digital twin modeling, global ubiquitous perception, data mapping, and model fusion are analyzed. With regard to the construction needs of Qingdao Port’s digital twin system, this paper presents a case study and illustrates the overall design process and function of the digital twin system for typical terminals. The system realizes the intelligent operation of the port with the core functions of three-dimensional visual monitoring and optimal dispatching based on real-time perception data. This paper serves as a feasible reference for future intelligent development of large ports and the application of digital twin technology.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. The Third Erasmus Smart Port Rotterdam (2014) Port Research Centre Rotterdam-Delft Poster Session, RDM Campus. The 3rd Erasmus Smart Port. Rotterdam: The Third Erasmus Smart Port Rotterdam, 1–123.

  2. Molavi A, Lim GJ, Race B (2020) A framework for building a smart port and smart port index. Int J Sustain Transp 14(9):686–700. https://doi.org/10.1080/15568318.2019.1610919

    Article  Google Scholar 

  3. Ding K, Chan FTS, Zhang XD, Zhou GH, Zhang FQ (2019) Defining a digital twin-based cyber-physical production system for autonomous manufacturing in smart shop floors. Int J Prod Res 57(20):6315–6334. https://doi.org/10.1080/00207543.2019.1566661

    Article  Google Scholar 

  4. Shafto M, Conroy M, Doyle R, Glaessgen E, Kemp C, LeMoigne J, Wang L (2012) Modeling, simulation, information technology & processing roadmap. Natl Aeronaut Space Adm 32:1–38

    Google Scholar 

  5. Schrotter G, Hürzeler C (2020) The digital twin of the city of Zurich for urban planning. PFG–J Photogramm, Remote Sens Geoinform Sci 88(1): 99–112. https://doi.org/10.1007/s41064-020-00092-2

  6. Tao F, Zhang M (2017) Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access 5:20418–20427. https://doi.org/10.1109/ACCESS.2017.2756069

    Article  Google Scholar 

  7. Yeo G, Lim SH, Wynter L, Hassan H (2019) MPA-IBM Project SAFER: sense-making analytics for maritime event recognition. Interfaces 49(4):269–280. https://doi.org/10.1287/inte.2019.0997

    Article  Google Scholar 

  8. Hofmann W, Branding F (2019) Implementation of an IoT- and cloud-based digital twin for real-time decision support in port operations. IFAC-PapersOnLine 52(13):2104–2109. https://doi.org/10.1016/j.ifacol.2019.11.516

    Article  Google Scholar 

  9. Chenhao Zhou, Loo Hay Lee, Ek Peng Chew (2019) Behind the scenes: research & development for Singapore Next Generation Port. 2019 World Transport Congress Proceedings (Part 1), pp 746–752

  10. Botti A, et al. (2017) The re-conceptualization of the port supply chain as a smart port service system: the case of the port of Salerno. Systems 5:35. https://doi.org/10.20944/preprints201704.0002.v1

  11. Fernández P, Santana JM, Ortega S et al (2016) SmartPort: a platform for sensor data monitoring in a seaport based on FIWARE. Sensors (Basel, Switzerland) 16(3):417. https://doi.org/10.3390/s16030417

    Article  Google Scholar 

  12. Zhang Q, Zhang X, Xu W, Liu A, Zhou Z, Pham DT (2017) Modeling of digital twin workshop based on perception data. In: Huang Y, Wu H, Liu H, Yin Z (eds) Intelligent robotics and applications. ICIRA 2017. Lecture Notes in Computer Science, vol 10464, pp 3–14. https://doi.org/10.1007/978-3-319-65298-6_1

  13. Port of Rotterdam puts Internet of Things platform into operation. https://www.portofrotterdam.com/en/news-and-press-releases/port-of-rotterdam-putsinternet-of-things-platform-into-operation. Accessed 31 Jan 2019

  14. Zhuang C, Liu J, Xiong H (2018) Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int J Adv Manuf Technol 96:1149–1163. https://doi.org/10.1007/s00170-018-1617-6

    Article  Google Scholar 

  15. Wang K et al (2021) Multi-aspect applications and development challenges of digital twin-driven management in global smart ports. Case Stud Transport Policy 9(3):1298–1312

    Article  Google Scholar 

  16. Abideen AZ, Sundram VPK, Pyeman J, Othman AK, Sorooshian S (2021) Digital twin integrated reinforced learning in supply chain and logistics. Logistics 5(4):84. https://doi.org/10.3390/logistics5040084

    Article  Google Scholar 

  17. Gao Y et al (2022) Design of digital twin applications in automated storage yard scheduling. Adv Eng Inform 51:101477

    Article  Google Scholar 

  18. Delbrügger T, Rossmann J (2019) Representing adaptation options in experimentable digital twins of production systems. Int J Computer Integr Manuf 32(4–5):352–365. https://doi.org/10.1080/0951192X.2019.1599433

    Article  Google Scholar 

  19. Zhou C et al (2021) Analytics with digital-twinning: a decision support system for maintaining a resilient port. Decis Support Syst 143:113496

    Article  Google Scholar 

  20. Redacción Opportimes: Port of Rotterdam: the Digital Twin. https://www.opportimes.com/port-of-rotterdam-the-digital-twin/. Accessed 22 July 2022

  21. Matthew Fennessy: A Digital Twin for Hamburg’s Port. https://www.uni-hamburg.de/en/newsroom/forschung/2022/0825-fv-11-projekt-hafenzwilling.html.Accessed 25 Aug 2022

  22. Grieves M (2015) Digital twin: manufacturing excellence through virtual factory replication. [Online]. Available: https://www.researchgate.net/publication/275211047. Digital Twin Manufacturing Excellence through Virtual Factory Replication

  23. Tao F et al (2018) Digital twin driven prognostics and health management for complex equipment. CIRP Ann 67(1):169–172. https://doi.org/10.1016/j.cirp.2018.04.055

    Article  Google Scholar 

  24. Redelinghuys AJH, Basson AH, Kruger K (2020) A six-layer architecture for the digital twin: a manufacturing case study implementation. J Intell Manuf 31:1383–1402. https://doi.org/10.1007/s10845-019-01516-6

    Article  Google Scholar 

  25. Negri E et al (2020) MES-integrated digital twin frameworks. J Manuf Syst 56:58–71. https://doi.org/10.1016/j.jmsy.2020.05.007

    Article  Google Scholar 

  26. Liu Q, Zhang H, Leng J, Chen X (2019) Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system. Int J Prod Res 57(12):3903–3919. https://doi.org/10.1080/00207543.2018.1471243

    Article  Google Scholar 

  27. Rasheed A, San O, Kvamsdal T (2020) Digital twin: values, challenges and enablers from a modeling perspective. IEEE Access 8:21980–22012. https://doi.org/10.1109/ACCESS.2020.2970143

    Article  Google Scholar 

  28. Huang S, Wang G, Lei D et al (2022) Toward digital validation for rapid product development based on digital twin: a framework. Int J Adv Manuf Technol 119:2509–2523. https://doi.org/10.1007/s00170-021-08475-4

    Article  Google Scholar 

  29. Bao J et al (2019) The modelling and operations for the digital twin in the context of manufacturing. Enterprise Inform Syst 13(4):534–556. https://doi.org/10.1080/17517575.2018.1526324

    Article  Google Scholar 

  30. Liu C et al (2020) Web-based digital twin modeling and remote control of cyber-physical production systems. Robot Computer-Integr Manuf 64:0736–5845. https://doi.org/10.1016/j.rcim.2020.101956

    Article  Google Scholar 

  31. Bao Q, Zhao G, Yu Y et al (2021) The ontology-based modeling and evolution of digital twin for assembly workshop. Int J Adv Manuf Technol 117:395–411. https://doi.org/10.1007/s00170-021-07773-1

    Article  Google Scholar 

  32. He B et al (2021) Data fusion-based sustainable digital twin system of intelligent detection robotics. J Clean Prod 280:124181. https://doi.org/10.1016/j.jclepro.2020.124181

    Article  Google Scholar 

  33. Liu J, Zhou H, Tian G et al (2019) Digital twin-based process reuse and evaluation approach for smart process planning. Int J Adv Manuf Technol 100:1619–1634. https://doi.org/10.1007/s00170-018-2748-5

    Article  Google Scholar 

  34. Nikolakis N, Alexopoulos K, Xanthakis E, Chryssolouris G (2019) The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor. Int J Comput Integr Manuf 32(1):1–12. https://doi.org/10.1080/0951192X.2018.1529430

    Article  Google Scholar 

Download references

Funding

This work is sponsored by National Key R&D Program of China (No. 2020YFB1710802) and Shanghai Key lab of Advanced Manufacturing Environment.

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Building of Mechanical Engineering Room A-715, DongChuan Road 800, MinHang District, Shanghai, 200240, China

    Wenqiang Yang, Xiangyu Bao & Yu Zheng

  2. Institute of Smart Manufacturing and Information Engineering, Shanghai Jiao Tong University, Shanghai, China

    Yu Zheng

  3. Shanghai Key Lab of Advanced Manufacturing Environment, Shanghai Jiao Tong University, Shanghai, China

    Yu Zheng

  4. Qingdao Port International Co., Ltd, Qingdao, 266011, China

    Lei Zhang

  5. Shandong Port Technology Group Qingdao Co., Ltd., Qingdao, 266011, China

    Ziqing Zhang

  6. China Waterborne Transport Research Institute, Beijing, 100088, China

    Zhao Zhang & Lin Li

Authors
  1. Wenqiang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangyu Bao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ziqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. the system structure conceive and digital twin system design were performed by Wenqiang Yang, Xiangyu Bao, and Yu Zheng. Material preparation and system deployment were performed by Lei Zhang and Ziqing Zhang. The network deployment and data collection were performed by Zhao Zhang and Lin Li. The first draft of the manuscript was written by Wenqiang Yang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yu Zheng.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, W., Bao, X., Zheng, Y. et al. A digital twin framework for large comprehensive ports and a case study of Qingdao Port. Int J Adv Manuf Technol 131, 5571–5588 (2024). https://doi.org/10.1007/s00170-022-10625-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-022-10625-1

Keywords

Search

Navigation