Abstract

In maritime studies, seafarer fatigue has been proven to be an important risk factor that affects human performance and leads to human errors. However, in the development of human reliability analysis (HRA) for the maritime industry, few studies have taken into account fatigue as a human performance-shaping factor (PSF) and systematically evaluate seafarer fatigue using HRA methods. In this paper, 52 ship masters and officers from six shipping companies are invited to select 15 leading influential factors as sub-PSFs from the 43 fatigue relevant factors within five categories (general PSFs) published by the International Maritime Organization (IMO). Next, the potential risk levels of the 15 sub-PSFs are evaluated and prioritized through a new failure modes and effects analysis (FMEA) method combining a belief-based Bayesian network (BBN) and an evidence reasoning (ER) algorithm. Finally, an axiomatic analysis is used to verify the robustness and applicability of the new FMEA method within the context of seafarer fatigue evaluation. It is found that the top five sub-PSFs include sleep quality, emotion, non-day shift, shift length, and noise, and it is suggested that these sub-PSFs should be integrated into maritime HRA analysis. The results of this study can not only promote navigation safety but also facilitate the development of fatigue risk management.

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Data Availability Statement

All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

Thanks to the experts from Mitsui O.S.K. Lines, Ltd. (MOL), Kawasaki Kisen Kaisha, Ltd. (‘K’ LINE), Nippon Yusen Kabushiki Kaisha (NYK line), Hachiuma Steamship Company Limited, Ocean Network Express Pte. Ltd. (ONE), and ‘K’ Line RoRo Bulk Ship Management Co. Ltd. (KRBS) for their strong support and patient feedback. This study was conducted while Renda Cui was an exchange student at the Maritime Human Factor laboratory of Kobe University, Japan. The study was under the supervision of Prof. Fuchi and assistant Prof. Konishi. Thanks for their rigorous and patient supervision. The authors gratefully acknowledge support from the National Natural Science Foundation of China (Grant No. 52101399), and the Fundamental Research Funds for the Central Universities (Grant No. 3132023138). This work was also supported by the EU H2020 ERC Consolidator Grant program (TRUST Grant No. 864724).

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9Issue 4December 2023

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Received: Mar 14, 2023
Accepted: Jun 23, 2023
Published online: Aug 23, 2023
Published in print: Dec 1, 2023
Discussion open until: Jan 23, 2024

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Ph.D. Student, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China. Email: [email protected]
Zhengjiang Liu [email protected]
Professor, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China. Email: [email protected]
Associate Professor, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China (corresponding author). ORCID: https://orcid.org/0000-0002-7469-6237. Email: [email protected]
Masaki Fuchi [email protected]
Professor, Maritime Science Faculty, Kobe Univ., Kobe, Hyogo 6578501, Japan. Email: [email protected]
Tsukasa Konishi [email protected]
Associate Professor, Maritime Science Faculty, Kobe Univ., Kobe, Hyogo 6578501, Japan. Email: [email protected]
Ph.D. Student, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China. Email: [email protected]
Juncheng Tao [email protected]
Ph.D. Student, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China. Email: [email protected]
Professor, Liverpool Logistics, Offshore, and Marine (LOOM) Research Institute, Liverpool John Moores Univ., Liverpool L3 3AF, UK; Part-time Professor, Transport Engineering College, Dalian Maritime Univ., Dalian 116026, PR China. ORCID: https://orcid.org/0000-0003-1385-493X. Email: [email protected]
Research Fellow, Liverpool Logistics, Offshore, and Marine (LOOM) Research Institute, Liverpool John Moores Univ., Liverpool L3 3AF, UK. ORCID: https://orcid.org/0000-0003-3714-7201. Email: [email protected]
Zhiwei Zhao [email protected]
Associate Professor, Transport Engineering College, Dalian Maritime Univ., Dalian 116026, PR China. Email: [email protected]

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