Ship-To-Ship Liquefied Natural Gas Bunkering Risk Assessment by Integrating Fuzzy Failure Mode and Effect Analysis and the Technique for Order Preference by Similarity to an Ideal Solution

An increasing demand can be observed in ship-to-ship (STS) liquefied natural gas (LNG) bunkering operations, and the failures involved may lead to considerable casualties or environmental damage. For this purpose, a comprehensive methodology is proposed in this study to identify and assess these failure modes. In detail, the STS LNG bunkering process is first decomposed to develop a hierarchical structure according to systems-theoretic process analysis (STPA), the results of which serve to identify potential failure modes and their causes. Then, all the failure modes are evaluated by experts in terms of occurrence, severity, and detectability to develop a fuzzy confidential matrix, which is then transferred as an explicit confidential matrix to be weighted and normalized. Finally, the risk levels of these failure modes are analyzed by relative closeness obtained from the technique for order preference by similarity to an ideal solution (TOPSIS). This study determines nine failure modes, all of which are ranked in terms of risk level. “High pressure in vapor return line”, and “High flow rate and leakage of LNG” are determined as the top two failure modes, with risk closeness values of 0.5791 and 0.5728, respectively. “Power failure for emergency valves” is ranked as the last one, with the risk closeness value being 0.5444. Finally, suggestions are proposed according to bunkering operation guidelines to prevent or control these failure modes.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-04-02
DOI
https://doi.org/10.3390/jmse13040710
Citations
8
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
11.19

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article

Ship-To-Ship Liquefied Natural Gas Bunkering Risk Assessment by Integrating Fuzzy Failure Mode and Effect Analysis and the Technique for Order Preference by Similarity to an Ideal Solution

Weiliang Qiao, Zichun Wang, F. Wei, Xinfeng Dai et al.
8 citations
Journal of Marine Science and Engineering
Risk and Safety Analysis
11.19
article

Ship-To-Ship Liquefied Natural Gas Bunkering Risk Assessment by Integrating Fuzzy Failure Mode and Effect Analysis and the Technique for Order Preference by Similarity to an Ideal Solution

Weiliang Qiao, Zichun Wang, F. Wei, Xinfeng Dai, Shengli Dong, Xiaoxue Ma
article en
8 citations

Abstract

An increasing demand can be observed in ship-to-ship (STS) liquefied natural gas (LNG) bunkering operations, and the failures involved may lead to considerable casualties or environmental damage. For this purpose, a comprehensive methodology is proposed in this study to identify and assess these failure modes. In detail, the STS LNG bunkering process is first decomposed to develop a hierarchical structure according to systems-theoretic process analysis (STPA), the results of which serve to identify potential failure modes and their causes. Then, all the failure modes are evaluated by experts in terms of occurrence, severity, and detectability to develop a fuzzy confidential matrix, which is then transferred as an explicit confidential matrix to be weighted and normalized. Finally, the risk levels of these failure modes are analyzed by relative closeness obtained from the technique for order preference by similarity to an ideal solution (TOPSIS). This study determines nine failure modes, all of which are ranked in terms of risk level. “High pressure in vapor return line”, and “High flow rate and leakage of LNG” are determined as the top two failure modes, with risk closeness values of 0.5791 and 0.5728, respectively. “Power failure for emergency valves” is ranked as the last one, with the risk closeness value being 0.5444. Finally, suggestions are proposed according to bunkering operation guidelines to prevent or control these failure modes.

Journal of Marine Science and EngineeringVol. 13(4)
Shanghai Ship and Shipping Research Institute (CN), Dalian Maritime University (CN)
China Postdoctoral Science Foundation, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 2%
Risk and Safety Analysis
11.19
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