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Improving Safety Management through Analysis of Near-Miss Reports—A Tanker Ship Case Study

Author

Listed:
  • Nermin Hasanspahić

    (Maritime Department, University of Dubrovnik, 20000 Dubrovnik, Croatia)

  • Srđan Vujičić

    (Maritime Department, University of Dubrovnik, 20000 Dubrovnik, Croatia)

  • Miho Kristić

    (Maritime Department, University of Dubrovnik, 20000 Dubrovnik, Croatia)

  • Mario Mandušić

    (Independent Researcher, 20000 Dubrovnik, Croatia)

Abstract

A near-miss management system (NMMS) is a tool used for improving safety at sea if adequately implemented. Valuable knowledge to improve safety management might be gained by investigating and analysing reported events. Therefore, it is of the utmost importance to report each observed near-miss event. Because tankers are generally considered dangerous, but at the same time safe due to stringent requirements, near-miss reports and NMMS policy were collected from one oil tanker ship. Data were pre-processed and analysed. Variables used during analysis were near-miss type, risk level, ship position, and onboard location of near-miss occurrence. Analysis of policy and reports revealed that most near misses occurred on the deck area, but higher-risk-level events were reported in the engine room and navigating bridge. Housekeeping, equipment failure, use of personal protective equipment (PPE), and process-/procedure-related events were most common and generally related to lower risk levels. The most frequent corrective actions recorded were implementing safe working practices and PPE. In addition, higher-risk-level events were related to less effective corrective actions. Based on the findings, suggestions for improvements include promoting safe behaviour and adequate PPE usage through additional training, ensuring proper housekeeping, regular maintenance of shipboard equipment and spare parts management, and toolbox meetings and risk assessments that include conclusions of near-miss investigations and analysis.

Suggested Citation

  • Nermin Hasanspahić & Srđan Vujičić & Miho Kristić & Mario Mandušić, 2022. "Improving Safety Management through Analysis of Near-Miss Reports—A Tanker Ship Case Study," Sustainability, MDPI, vol. 14(3), pages 1-19, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1094-:d:727677
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    References listed on IDEAS

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    1. Junayed Pasha & Maxim A. Dulebenets & Masoud Kavoosi & Olumide F. Abioye & Oluwatosin Theophilus & Hui Wang & Raphael Kampmann & Weihong Guo, 2020. "Holistic tactical-level planning in liner shipping: an exact optimization approach," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-35, December.
    2. Dulebenets, Maxim A., 2018. "A comprehensive multi-objective optimization model for the vessel scheduling problem in liner shipping," International Journal of Production Economics, Elsevier, vol. 196(C), pages 293-318.
    3. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    Cited by:

    1. Karolien van Nunen & Genserik Reniers & Koen Ponnet, 2022. "Measuring Safety Culture Using an Integrative Approach: The Development of a Comprehensive Conceptual Framework and an Applied Safety Culture Assessment Instrument," IJERPH, MDPI, vol. 19(20), pages 1-39, October.

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