IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0307059.html
   My bibliography  Save this article

Visualization system to identify structurally vulnerable links in OHT railway network in semiconductor FAB using betweenness centrality

Author

Listed:
  • Jinwoo Choi
  • Youngbin Park
  • Yeeun Choi
  • Sehyeon Kim
  • Heewon Lee
  • Hyunwoo Park

Abstract

In semiconductor fabrication (FAB), wafers are placed into carriers known as Front Opening Unified Pods (FOUPs), transported by the Overhead Hoist Transport (OHT). The OHT, a type of Automated Guided Vehicle (AGV), moves along a fixed railway network in the FAB. The routes of OHTs on the railway network are typically determined by a Single Source Shortest Path (SSSP) algorithm such as Dijkstra’s. However, the presence of hundreds of operating OHTs often leads to path interruptions, causing congestion or deadlocks that ultimately diminish the overall productivity of the FAB. This research focused on identifying structurally vulnerable links within the OHT railway network in semiconductor FAB and developing a visualization system for enhanced on-site decision-making. We employed betweenness centrality as a quantitative index to evaluate the structural vulnerability of the OHT railway network. Also, to accommodate the unique hierarchical node-port structure of this network, we modified the traditional Brandes algorithm, a widely-used method for calculating betweenness centrality. Our modification of the Brandes algorithm integrated node-port characteristics without increasing computation time while incorporating parallelization to reduce computation time further and improve usability. Ultimately, we developed an end-to-end web-based visualization system that enables users to perform betweenness centrality calculations on specific OHT railway layouts using our algorithm and view the results through a web interface. We validated our approach by comparing our results with historically vulnerable links provided by Samsung Electronics. The study had two main outcomes: the development of a new betweenness centrality calculation algorithm considering the node-port structure and the creation of a visualization system. The study demonstrated that the node-port structure betweenness centrality effectively identified vulnerable links in the OHT railway network. Presenting these findings through a visualization system greatly enhanced their practical applicability and relevance.

Suggested Citation

  • Jinwoo Choi & Youngbin Park & Yeeun Choi & Sehyeon Kim & Heewon Lee & Hyunwoo Park, 2024. "Visualization system to identify structurally vulnerable links in OHT railway network in semiconductor FAB using betweenness centrality," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-19, July.
    • Handle: RePEc:plo:pone00:0307059
    DOI: 10.1371/journal.pone.0307059
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0307059
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0307059&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0307059?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    2. Kyuree Ahn & Kanghoon Lee & Juneyoung Yeon & Jinkyoo Park, 2022. "Congestion-aware dynamic routing for an overhead hoist transporter system using a graph convolutional gated recurrent unit," IISE Transactions, Taylor & Francis Journals, vol. 54(8), pages 803-816, August.
    3. Szymula, Christopher & Bešinović, Nikola, 2020. "Passenger-centered vulnerability assessment of railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 30-61.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alessandra Cornaro & Daniele Grechi, 2023. "Evaluation of Railway Systems: A Network Approach," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    2. Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    3. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.
    4. Bergström, Anna & Krüger, Niclas A., 2013. "Modeling passenger train delay distributions: evidence and implications," Working papers in Transport Economics 2013:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    5. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    6. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    7. Mengying Cui & David Levinson, 2018. "Accessibility analysis of risk severity," Transportation, Springer, vol. 45(4), pages 1029-1050, July.
    8. Milan Janić, 2018. "Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events: the case of HSR (high speed rail)," Transportation, Springer, vol. 45(4), pages 1101-1137, July.
    9. Masiero, Lorenzo & Maggi, Rico, 2012. "Estimation of indirect cost and evaluation of protective measures for infrastructure vulnerability: A case study on the transalpine transport corridor," Transport Policy, Elsevier, vol. 20(C), pages 13-21.
    10. Jing Liu & Huapu Lu & Mingyu Chen & Jianyu Wang & Ying Zhang, 2020. "Macro Perspective Research on Transportation Safety: An Empirical Analysis of Network Characteristics and Vulnerability," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    11. Tan, Erlong & Liu, Bing & Guo, Cong & Ma, Xiaolei, 2024. "Restoration sequence optimization for vulnerable metro stations with limited budget: A case study of Beijing, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    12. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    13. Jenelius, Erik, 2010. "User inequity implications of road network vulnerability," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 57-73.
    14. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    15. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    16. Mylonas, Chrysostomos & Mitsakis, Evangelos & Kepaptsoglou, Konstantinos, 2023. "Criticality analysis in road networks with graph-theoretic measures, traffic assignment, and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    17. Chan, Ho-Yin & Ma, Hanxi & Zhou, Jiangping, 2024. "Resilience of socio-technical transportation systems: A demand-driven community detection in human mobility structures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    18. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    19. Roberto Cardinale, 2022. "State-Owned Enterprises’ Reforms and their Implications for the Resilience and Vulnerability of the Chinese Economy: Evidence from the Banking, Energy and Telecom Sectors," Networks and Spatial Economics, Springer, vol. 22(3), pages 489-514, September.
    20. repec:plo:pone00:0188790 is not listed on IDEAS
    21. Rolf Nyberg & Magnus Johansson, 2013. "Indicators of road network vulnerability to storm-felled trees," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(1), pages 185-199, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0307059. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.