IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v231y2023ics0951832022005907.html
   My bibliography  Save this article

Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach

Author

Listed:
  • Elidolu, Gizem
  • Sezer, Sukru Ilke
  • Akyuz, Emre
  • Arslan, Ozcan
  • Arslanoglu, Yasin

Abstract

Ballasting and de-ballasting operations play a critical role in maintaining stability and safety onboard tanker vessels. The process involves considerable risks to human health, the marine environment and property since the failures during the operation may lead to loss of equipment, serious balance defection and related safety problems, and harm to the coastal ecosystems. In this context, this paper aims to fill the gap concerning this problem by analyzing the operational risks of ballasting and de-ballasting performed on tanker ships. It is utilized a robust methodological approach, Failure Mode Effects and Criticality Analysis (FMECA) to provide a detailed insight into operational hazards, and Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) to tackle with limitations of FMECA by evaluating the hazards’ importance degrees. The highest-ranked risks are found as “unsynchronized cargo and ballast operation†with a crisp risk value of 50.59 and “excessive list during cargo operation†with 47.08 crisp risk value, while the least crisp risk valued (21.94) failure is “undetected blockage of air vents†. Besides its robust theoretical background, the paper provides valuable insights to tanker officers, shipowners, safety and technical inspectors to minimize risks and enhance safety at the operational level onboard tanker vessels.

Suggested Citation

  • Elidolu, Gizem & Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan & Arslanoglu, Yasin, 2023. "Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    • Handle: RePEc:eee:reensy:v:231:y:2023:i:c:s0951832022005907
    DOI: 10.1016/j.ress.2022.108975
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832022005907
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2022.108975?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. Cunlong Fan & Jakub Montewka & Di Zhang, 2021. "Towards a Framework of Operational-Risk Assessment for a Maritime Autonomous Surface Ship," Energies, MDPI, vol. 14(13), pages 1-12, June.
    2. Aziz, Abdul & Ahmed, Salim & Khan, Faisal & Stack, Chris & Lind, Annes, 2019. "Operational risk assessment model for marine vessels," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 348-361.
    3. Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan, 2022. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    4. Hassan, Shamsu & Wang, Jin & Kontovas, Christos & Bashir, Musa, 2022. "An assessment of causes and failure likelihood of cross-country pipelines under uncertainty using bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    5. 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).
    6. 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).
    7. Chi, Chia-Fen & Sigmund, Davin & Astardi, Martin Octavianus, 2020. "Classification Scheme for Root Cause and Failure Modes and Effects Analysis (FMEA) of Passenger Vehicle Recalls," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    8. Emre Akyuz & Erkan Celik, 2018. "A quantitative risk analysis by using interval type-2 fuzzy FMEA approach: the case of oil spill," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(8), pages 979-994, November.
    9. Silveira, P. & Teixeira, A.P. & Figueira, J.R. & Guedes Soares, C., 2021. "A multicriteria outranking approach for ship collision risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    10. 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).
    11. 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).
    12. Zhou, Yusheng & Li, Xue & Yuen, Kum Fai, 2022. "Holistic risk assessment of container shipping service based on Bayesian Network Modelling," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    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. Li, Siqi & Wang, Junfeng & Rong, Jin, 2024. "Combining improved DFMEA with knowledge graph for component risk analysis of complex products," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    2. Zhang, Jinfeng & Jin, Mei & Wan, Chengpeng & Dong, Zhijie & Wu, Xiaohong, 2024. "A Bayesian network-based model for risk modeling and scenario deduction of collision accidents of inland intelligent ships," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Deng, Wanyi & Ma, Xiaoxue & Qiao, Weiliang, 2024. "A novel methodology to quantify the impact of safety barriers on maritime operational risk based on a probabilistic network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Domeh, Vindex & Obeng, Francis & Khan, Faisal & Bose, Neil & Sanli, Elizabeth, 2023. "An operational risk awareness tool for small fishing vessels operating in harsh environment," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. She, Jianjun & Guo, Zihao & Li, Zhijian & Liang, Shuwei & Zhou, Yilun, 2024. "Research on scenario deduction and emergency decision-making evaluation for construction safety accidents," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    6. Li, Yuwan & Yuen, Kum Fai & Zhou, Yusheng, 2024. "Risk assessment of achieving greenhouse gas emission reduction target in the maritime industry," Transport Policy, Elsevier, vol. 155(C), pages 29-46.

    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. Uflaz, Esma & Sezer, Sukru Ilke & Tunçel, Ahmet Lutfi & Aydin, Muhammet & Akyuz, Emre & Arslan, Ozcan, 2024. "Quantifying potential cyber-attack risks in maritime transportation under Dempster–Shafer theory FMECA and rule-based Bayesian network modelling," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. 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).
    3. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. 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).
    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. Bhattacharjee, Pushparenu & Dey, Vidyut & Mandal, U.K. & Paul, Susmita, 2022. "Quantitative risk assessment of submersible pump components using Interval number-based Multinomial Logistic Regression(MLR) model," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    7. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Xin, Xuri & Liu, Kezhong & Loughney, Sean & Wang, Jin & Li, Huanhuan & Ekere, Nduka & Yang, Zaili, 2023. "Multi-scale collision risk estimation for maritime traffic in complex port waters," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    9. Adhita, I Gde Manik Sukanegara & Fuchi, Masaki & Konishi, Tsukasa & Fujimoto, Shoji, 2023. "Ship navigation from a Safety-II perspective: A case study of training-ship operation in coastal area," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    10. Liang, Xinrui & Fan, Shiqi & Lucy, John & Yang, Zaili, 2022. "Risk analysis of cargo theft from freight supply chains using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    11. Montewka, Jakub & Manderbacka, Teemu & Ruponen, Pekka & Tompuri, Markus & Gil, Mateusz & Hirdaris, Spyros, 2022. "Accident susceptibility index for a passenger ship-a framework and case study," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    12. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    13. Li, Baode & Lu, Jing & Li, Jing & Zhu, Xuebin & Huang, Chuan & Su, Wan, 2022. "Scenario evolutionary analysis for maritime emergencies using an ensemble belief rule base," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    14. Guo, Yunlong & Jin, Yongxing & Hu, Shenping & Yang, Zaili & Xi, Yongtao & Han, Bing, 2023. "Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    15. 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).
    16. Xiaoyuan Zhao & Haiwen Yuan & Qing Yu, 2021. "Autonomous Vessels in the Yangtze River: A Study on the Maritime Accidents Using Data-Driven Bayesian Networks," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
    17. Xu, Sheng & Kim, Ekaterina & Haugen, Stein & Zhang, Mingyang, 2022. "A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    18. Ballester-Ripoll, Rafael & Leonelli, Manuele, 2022. "Computing Sobol indices in probabilistic graphical models," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    19. Kandel, Rajesh & Baroud, Hiba, 2024. "A data-driven risk assessment of Arctic maritime incidents: Using machine learning to predict incident types and identify risk factors," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    20. Yang, Zhisen & Wan, Chengpeng & Yang, Zaili & Yu, Qing, 2021. "Using Bayesian network-based TOPSIS to aid dynamic port state control detention risk control decision," 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:231:y:2023:i:c:s0951832022005907. 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.