IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v169y2018icp485-502.html
   My bibliography  Save this article

An operational risk analysis tool to analyze marine transportation in Arctic waters

Author

Listed:
  • Khan, Bushra
  • Khan, Faisal
  • Veitch, Brian
  • Yang, Ming

Abstract

The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable climatic changes, and remoteness. Considering the high degree of uncertainty in the performance of vessel operating systems and humans, robust risk analysis and management tools are required to provide decision-support to prevent accidents and ensure safety at sea. This paper proposes an Object-Oriented Bayesian Network model to dynamically predict ship-ice collision probability based on navigational and operational system states, weather and ice conditions, and human error. The model, when integrated with potential consequences, may help estimate risk. A case study related to oil tanker navigation on the Northern Sea Route (NSR) is used to show the application of the proposed model to predict oil tanker collision with sea ice.

Suggested Citation

  • Khan, Bushra & Khan, Faisal & Veitch, Brian & Yang, Ming, 2018. "An operational risk analysis tool to analyze marine transportation in Arctic waters," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 485-502.
    • Handle: RePEc:eee:reensy:v:169:y:2018:i:c:p:485-502
    DOI: 10.1016/j.ress.2017.09.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017303101
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2017.09.014?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Trucco, P. & Cagno, E. & Ruggeri, F. & Grande, O., 2008. "A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 845-856.
    2. Aven, Terje, 2008. "A semi-quantitative approach to risk analysis, as an alternative to QRAs," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 790-797.
    3. Montewka, Jakub & Ehlers, Sören & Goerlandt, Floris & Hinz, Tomasz & Tabri, Kristjan & Kujala, Pentti, 2014. "A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 142-157.
    4. Goerlandt, Floris & Montewka, Jakub, 2015. "Maritime transportation risk analysis: Review and analysis in light of some foundational issues," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 115-134.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adland, Roar & Jia, Haiying & Lode, Tønnes & Skontorp, Jørgen, 2021. "The value of meteorological data in marine risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Hossain, Niamat Ullah Ibne & Jaradat, Raed & Hosseini, Seyedmohsen & Marufuzzaman, Mohammad & Buchanan, Randy K., 2019. "A framework for modeling and assessing system resilience using a Bayesian network: A case study of an interdependent electrical infrastructure system," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 62-83.
    3. Yu, Qing & Liu, Kezhong & Chang, Chia-Hsun & Yang, Zaili, 2020. "Realising advanced risk assessment of vessel traffic flows near offshore wind farms," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Carine Dominguez-Péry & Lakshmi Narasimha Raju Vuddaraju & Isabelle Corbett-Etchevers & Rana Tassabehji, 2021. "Reducing maritime accidents in ships by tackling human error: a bibliometric review and research agenda," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-32, December.
    5. Koçak, Saim Turgut & Yercan, Funda, 2021. "Comparative cost-effectiveness analysis of Arctic and international shipping routes: A Fuzzy Analytic Hierarchy Process," Transport Policy, Elsevier, vol. 114(C), pages 147-164.
    6. Maroua Ghram & Hela Moalla Frikha, 2022. "Multiple Hierarchically Structured Criteria in ARAS Method Under Fuzzy Environment," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 11(1), pages 1-19, January.
    7. Zvyagina, Tatiana & Zvyagin, Petr, 2022. "A model of multi-objective route optimization for a vessel in drifting ice," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    8. Rajesh S. Prabhu Gaonkar & V. Mariappan, 0. "Transportation time reliability appraisal in maritime context," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-11.
    9. Zhang, Chi & Zhang, Di & Zhang, Mingyang & Lang, Xiao & Mao, Wengang, 2020. "An integrated risk assessment model for safe Arctic navigation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 101-114.
    10. Zhu, Chunli & Wu, Jianping & Liu, Mingyu & Luan, Jianlin & Li, Tingting & Hu, Kezhen, 2020. "Cyber-physical resilience modelling and assessment of urban roadway system interrupted by rainfall," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    11. Ung, S.T., 2021. "Navigation Risk estimation using a modified Bayesian Network modeling-a case study in Taiwan," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    12. Zhou, Jian-Lan & Lei, Yi, 2020. "A slim integrated with empirical study and network analysis for human error assessment in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    13. Yu, Qing & Teixeira, Ângelo Palos & Liu, Kezhong & Rong, Hao & Guedes Soares, Carlos, 2021. "An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    14. Li, Jue & Li, Heng & Wang, Fan & Cheng, Andy S.K. & Yang, Xincong & Wang, Hongwei, 2021. "Proactive analysis of construction equipment operators’ hazard perception error based on cognitive modeling and a dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    15. Benz, Lukas & Münch, Christopher & Hartmann, Evi, 2021. "Fuzzy-based decision analysis on Arctic transportation: A guidance for freight shipping companies," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 375-400, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    16. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    17. Rajesh S. Prabhu Gaonkar & V. Mariappan, 2020. "Transportation time reliability appraisal in maritime context," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 736-746, June.
    18. Hossain, Niamat Ullah Ibne & Nur, Farjana & Hosseini, Seyedmohsen & Jaradat, Raed & Marufuzzaman, Mohammad & Puryear, Stephen M., 2019. "A Bayesian network based approach for modeling and assessing resilience: A case study of a full service deep water port," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 378-396.
    19. Dinis, D. & Teixeira, A.P. & Guedes Soares, C., 2020. "Probabilistic approach for characterising the static risk of ships using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    20. Zhuang Li & Shenping Hu & Guoping Gao & Yongtao Xi & Shanshan Fu & Chenyang Yao, 2020. "Risk Reasoning from Factor Correlation of Maritime Traffic under Arctic Sea Ice Status Association with a Bayesian Belief Network," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    21. Li, Zhongping & Cui, Lirong & Chen, Jianhui, 2018. "Traffic accident modelling via self-exciting point processes," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 312-320.
    22. Tao, Longlong & Chen, Liwei & Ge, Daochuan & Yao, Yuantao & Ruan, Fang & Wu, Jie & Yu, Jie, 2022. "An integrated probabilistic risk assessment methodology for maritime transportation of spent nuclear fuel based on event tree and hydrodynamic model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).

    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. Dinis, D. & Teixeira, A.P. & Guedes Soares, C., 2020. "Probabilistic approach for characterising the static risk of ships using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    2. Jinfen Zhang & Ângelo P Teixeira & C. Guedes Soares & Xinping Yan & Kezhong Liu, 2016. "Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1171-1187, June.
    3. Yu, Qing & Teixeira, Ângelo Palos & Liu, Kezhong & Rong, Hao & Guedes Soares, Carlos, 2021. "An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    7. Bing Wu & Huibin Tian & Xinping Yan & C. Guedes Soares, 2020. "A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian Networks," Journal of Risk and Reliability, , vol. 234(2), pages 422-436, April.
    8. Fan, Shiqi & Blanco-Davis, Eduardo & Yang, Zaili & Zhang, Jinfen & Yan, Xinping, 2020. "Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    9. Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2022. "Maritime traffic probabilistic prediction based on ship motion pattern extraction," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    10. Mauro, Francesco & Vassalos, Dracos & Paterson, Donald, 2022. "Critical damages identification in a multi-level damage stability assessment framework for passenger ships," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    11. Yamin Huang & P. H. A. J. M. van Gelder, 2020. "Time‐Varying Risk Measurement for Ship Collision Prevention," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 24-42, January.
    12. Yu, Qing & Liu, Kezhong & Chang, Chia-Hsun & Yang, Zaili, 2020. "Realising advanced risk assessment of vessel traffic flows near offshore wind farms," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    13. Jieyin Lyu & Fuli Zhou & Yandong He, 2023. "Digital Technique-Enabled Container Logistics Supply Chain Sustainability Achievement," Sustainability, MDPI, vol. 15(22), pages 1-28, November.
    14. Valdez Banda, Osiris A. & Kannos, Sirpa & Goerlandt, Floris & van Gelder, Pieter H.A.J.M. & Bergström, Martin & Kujala, Pentti, 2019. "A systemic hazard analysis and management process for the concept design phase of an autonomous vessel," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    15. Berner, Christine Louise & Flage, Roger, 2016. "Comparing and integrating the NUSAP notational scheme with an uncertainty based risk perspective," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 185-194.
    16. Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2021. "Spatial correlation analysis of near ship collision hotspots with local maritime traffic characteristics," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    17. Zvyagina, Tatiana & Zvyagin, Petr, 2022. "A model of multi-objective route optimization for a vessel in drifting ice," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    18. Li, Zhongping & Cui, Lirong & Chen, Jianhui, 2018. "Traffic accident modelling via self-exciting point processes," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 312-320.
    19. Shiqi Fan & Zaili Yang & Eduardo Blanco-Davis & Jinfen Zhang & Xinping Yan, 2020. "Analysis of maritime transport accidents using Bayesian networks," Journal of Risk and Reliability, , vol. 234(3), pages 439-454, June.
    20. Zhang, Mingyang & Montewka, Jakub & Manderbacka, Teemu & Kujala, Pentti & Hirdaris, Spyros, 2021. "A Big Data Analytics Method for the Evaluation of Ship - Ship Collision Risk reflecting Hydrometeorological Conditions," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

    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:eee:reensy:v:169:y:2018:i:c:p:485-502. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.