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1- Department of Maritime Engineering, Amirkabir University of Technology
Abstract: (17 Views)
Commercial fishing vessels account for 44% of global seafarer fatalities despite comprising only 2.3% of the merchant fleet, with equipment failure contributing to 31% of fatal incidents. The FMEA method critically underperforms in this context due to implicit equal weighting, non-unique Risk Priority Number (RPN) mapping, and subjective weight assignment. This study validates an integrated CRITIC-CODAS-FMEA framework, building on our prior application to composite Lenj hulls, by extending robust proof across navigation, refrigeration, and propulsion subsystems of fishing Lenj. Almost all failure modes are analyzed using expert elicitation (n=12 marine specialists). The CRITIC method derives objective weights by quantifying contrast intensity and inter-criterion conflict in S/O/D ratings, while the CODAS method employed Euclidean and Taxicab distances to resolve ranking ambiguities in the weighted space. The framework achieves 100% resolution of identical RPN clusters and elevates 89% of high-severity modes (S≥9) into top-10 rankings versus 60% for conventional FMEA. It demonstrated superior alignment with expert consensus (Spearman ρ=0.87 vs. 0.62) and 92% expert agreement versus 56% for RPN-based prioritization. This framework transforms risk assessment into a context-aware decision tool, objectively capturing marine operational realities to significantly enhance crew safety for the 34.3 million fishers operating worldwide.
Keywords: Maritime Safety, FMEA, CRITIC, CODAS, Multi-Criteria Decision Making (MCDM), Fishing Lenj.
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Highlights
- CRITIC‑CODAS‑FMEA resolves identical RPN clusters across fishing‑vessel failure modes.
- CRITIC derives objective subsystem‑specific weights, eliminating subjective weighting.
- CODAS dual‑distance ranking elevates high‑severity modes into top rankings versus conventional FMEA.
- Rankings align with expert consensus.
- Context‑aware prioritization transforms FMEA into a crew‑safety decision tool for commercial fishing fleets.
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References
1. [1] F. Wang et al., "Identification of Risk Influential Factors for Fishing Vessel Accidents Using Claims Data from Fishery Mutual Insurance Association," Sustainability, vol. 15, no. 18, p. 13427, Sep. 2023, doi: 10.3390/su151813427. [DOI:10.3390/su151813427]
2. [2] S.-H. Kim, S.-H. Lee, K.-J. Ryu, and Y.-W. Lee, "Analysis of Accidents of Fishing Vessels Caused by Human Elements in Korean Sea Area," J. Mar. Sci. Eng., vol. 12, no. 9, p. 1564, Sep. 2024, doi: 10.3390/jmse12091564. [DOI:10.3390/jmse12091564]
3. [3] V. Domeh, F. Obeng, F. Khan, N. Bose, and E. Sanli, "A novel methodology to develop risk-based maintenance strategies for fishing vessels," Ocean Eng., vol. 253, p. 111281, Jun. 2022, doi: 10.1016/j.oceaneng.2022.111281. [DOI:10.1016/j.oceaneng.2022.111281]
4. [4] G. Vizentin and D. Vukelić, "Marine environment induced failure of FRP composites used in maritime transport," Eng. Fail. Anal., vol. 137, p. 106258, 2022, doi: 10.1016/j.engfailanal.2022.106258. [DOI:10.1016/j.engfailanal.2022.106258]
5. [5] Z. Han, J. Jang, J. R. G. Souppez, and H. Seo, "Comparison of structural design and future trends in composite hulls : A regulatory review," Int. J. Nav. Archit. Ocean Eng., vol. 15, no. March, p. 100558, 2023, doi: 10.1016/j.ijnaoe.2023.100558. [DOI:10.1016/j.ijnaoe.2023.100558]
6. [6] Z. Zhang, H. Zhu, and H. Liang, "Blockchain-Based Cold Chain Traceability with NR-PBFT and IoV-IMS for Marine Fishery Vessels," J. Mar. Sci. Eng., vol. 12, no. 8, p. 1371, Aug. 2024, doi: 10.3390/jmse12081371. [DOI:10.3390/jmse12081371]
7. [7] F. Obeng, D. Domeh, F. Khan, N. Bose, and E. Sanli, "An operational risk management approach for small fishing vessel," Reliab. Eng. Syst. Saf., vol. 247, p. 110104, 2024, doi:
https://doi.org/10.1016/j.ress.2024.110104 [DOI:10.1016/j.ress.2024.110104.]
8. [8] H. Wang, N. Chen, B. Wu, and C. Guedes Soares, "Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model," Reliab. Eng. Syst. Saf., vol. 249, p. 110201, 2024, doi:
https://doi.org/10.1016/j.ress.2024.110201 [DOI:10.1016/j.ress.2024.110201.]
9. [9] X. Li, Z. Han, M. Yazdi, and G. Chen, "A CRITIC-VIKOR based robust approach to support risk management of subsea pipelines," Appl. Ocean Res., vol. 124, p. 103187, 2022, doi:
https://doi.org/10.1016/j.apor.2022.103187 [DOI:10.1016/j.apor.2022.103187.]
10. [10] S. G. Wang and R. Z. Wang, "Recent developments of refrigeration technology in fishing vessels," Renew. Energy, vol. 30, pp. 589-600, 2005, doi: 10.1016/j.renene.2004.03.020. [DOI:10.1016/j.renene.2004.03.020]
11. [11] V. Anes and A. Abreu, "A Hybrid FMEA-ROC-CoCoSo Approach for Improved Risk Assessment and Reduced Complexity in Failure Mode Prioritization," Algorithms 2024, Vol. 17, Page 585, vol. 17, no. 12, p. 585, Dec. 2024, doi: 10.3390/A17120585. [DOI:10.3390/a17120585]
12. [12] E. Akdamar, G. Elidolu, M. Gögebakan, and B. O. Ceylan, "Entropy-based borda extended weighted expert FMEA approach: Comparison with classical and fuzzy FMEA on a ship system," Appl. Soft Comput., vol. 188, p. 114424, Feb. 2026, doi: 10.1016/J.ASOC.2025.114424. [DOI:10.1016/j.asoc.2025.114424]
13. [13] V. Karanović, B. O. Ceylan, and M. Jocanović, "Reliable ships: A fuzzy FMEA based risk analysis on four-ram type hydraulic steering system," Ocean Eng., vol. 314, p. 119758, 2024, doi:
https://doi.org/10.1016/j.oceaneng.2024.119758 [DOI:10.1016/j.oceaneng.2024.119758.]
14. [14] A. Laakso, M. Chaal, and O. A. Valdez Banda, "A risk assessment of an autonomous navigation system for a maritime autonomous surface ship," J. Mar. Eng. Technol., vol. 24, no. 4, pp. 253-269, Jul. 2025, doi: 10.1080/20464177.2025.2460268. [DOI:10.1080/20464177.2025.2460268]
15. [15] H. Li, H. Díaz, and C. Guedes Soares, "A failure analysis of floating offshore wind turbines using AHP-FMEA methodology," Ocean Eng., vol. 234, p. 109261, 2021, doi:
https://doi.org/10.1016/j.oceaneng.2021.109261 [DOI:10.1016/j.oceaneng.2021.109261.]
16. [16] S. I. Sezer, "An extended failure mode and effects analysis (FMEA) combining cloud model, AHP and TOPSIS for cargo discharge operation failure," Ocean Eng., vol. 356, p. 125334, 2026, doi:
https://doi.org/10.1016/j.oceaneng.2026.125334 [DOI:10.1016/j.oceaneng.2026.125334.]
17. [17] Q. Fu, Y. Sun, and L. Wang, "Risk Assessment of Import Cold Chain Logistics Based on Entropy Weight Matter Element Extension Model: A Case Study of Shanghai, China," Int. J. Environ. Res. Public Heal. 2022, Vol. 19, Page 16892, vol. 19, no. 24, p. 16892, Dec. 2022, doi: 10.3390/IJERPH192416892. [DOI:10.3390/ijerph192416892] [PMID] [PMCID]
18. [18] Z. Zhang, Y. Sun, L. Sun, Y. Guo, and J. Kang, "Research on the failure modes of autonomous navigation equipment based on the improved expert evaluation method," Ocean Eng., vol. 300, p. 117375, May 2024, doi: 10.1016/J.OCEANENG.2024.117375. [DOI:10.1016/j.oceaneng.2024.117375]
19. [19] A. R. Krishnan, M. M. Kasim, R. Hamid, and M. F. Ghazali, "A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria," Symmetry (Basel)., vol. 13, no. 6, p. 973, May 2021, doi: 10.3390/sym13060973. [DOI:10.3390/sym13060973]
20. [20] A. Pillay and J. Wang, "Modified failure mode and effects analysis using approximate reasoning," Reliab. Eng. Syst. Saf., vol. 79, no. 1, pp. 69-85, Jan. 2003, doi: 10.1016/S0951-8320(02)00179-5. [DOI:10.1016/S0951-8320(02)00179-5]
21. [21] G. Jin, Q. Meng, and W. Feng, "Optimization of Logistics System with Fuzzy FMEA-AHP Methodology," Process. 2022, Vol. 10, Page 1973, vol. 10, no. 10, p. 1973, Sep. 2022, doi: 10.3390/PR10101973. [DOI:10.3390/pr10101973]
22. [22] J. H. Zhu, Z. S. Chen, B. Shuai, W. Pedrycz, K. S. Chin, and L. Martínez, "Failure mode and effect analysis: A three-way decision approach," Eng. Appl. Artif. Intell., vol. 106, p. 104505, Nov. 2021, doi: 10.1016/J.ENGAPPAI.2021.104505. [DOI:10.1016/j.engappai.2021.104505]
23. [23] J. Roy, S. Das, S. Kar, and D. Pamučar, "An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information," Symmetry 2019, Vol. 11, Page 393, vol. 11, no. 3, p. 393, Mar. 2019, doi: 10.3390/SYM11030393. [DOI:10.3390/sym11030393]
24. [24] S. H. Gurmani, S. Zhang, F. A. Awwad, and E. A. A. Ismail, "Combinative distance-based assessment method using linguistic T-spherical fuzzy aggregation operators and its application to multi-attribute group decision-making," Eng. Appl. Artif. Intell., vol. 133, p. 108165, Jul. 2024, doi: 10.1016/J.ENGAPPAI.2024.108165. [DOI:10.1016/j.engappai.2024.108165]
25. [25] M. Keshavarz Ghorabaee, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, "A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making," Econ. Comput. Econ. Cybern. Stud. Res., vol. 50, no. 3, pp. 25-44, 2016.
26. [26] E. Shafizade and S. Hossein Mousavizadegan, "A comprehensive risk assessment framework for composite Lenj Hulls: integrating FMEA with CRITIC-CODAS," Civ. Eng. Environ. Syst., vol. 42, no. 3-4, pp. 314-334, Oct. 2025, doi: 10.1080/10286608.2025.2548230. [DOI:10.1080/10286608.2025.2548230]
27. [27] W. Jiang, C. Xie, M. Zhuang, and Y. Tang, "Failure mode and effects analysis based on a novel fuzzy evidential method," Appl. Soft Comput., vol. 57, pp. 672-683, Aug. 2017, doi: 10.1016/J.ASOC.2017.04.008. [DOI:10.1016/j.asoc.2017.04.008]
28. [28] FAO, "The State of World Fisheries and Aquaculture 2022: Towards Blue Transformation," 2022. doi: 10.4060/cc0461en. [DOI:10.4060/cc0461en]
29. [29] T. W. Chang, H. W. Lo, K. Y. Chen, and J. J. H. Liou, "A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment," Mathematics, vol. 7, no. 10, pp. 1-21, 2019, doi: 10.3390/math7100874. [DOI:10.3390/math7100874]
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