Application of Rough Set Theory and Bow-Tie Analysis to Maritime Safety Analysis Management: A Case Study of Taiwan Ship Collision Incidents
Source abstract
Abstract
The surrounding waters of Taiwan are evaluated as a moderate risk environment by Casualty Return, Lloyd’s Registry of Shipping. Among all types of maritime accidents, ship collisions occur most often, which has severe consequences, including ship damage, sinking and death of crews, and destruction of marine environments. It is, therefore, imperative to mitigate the risk of ship collision by exploring the risk factors and then providing preventive measures. This study invited domain experts to form a decision-making group, which helped with the risk assessment. The initial set of risk factors was selected from the literature. The expert group then identified seven representative risk factors using rough set theory (RST). The researchers worked with the experts to delineate the diagram of a bow-tie analysis (BTA), which provided the causes, consequences, and preventive and mitigation measures for ship collision incidents. The results show an integrated research framework for the risk assessment of ship collision that can effectively identify key factors and associated managerial strategies to improve navigation safety, leading to a sound marine environment.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Maritime Navigation and Safety · Structural Integrity and Reliability Analysis · Oil Spill Detection and Mitigation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Marine Environment and Engineering, National Sun Yat-sen University, No. 70, Lienhai Rd., Kaohsiung 80424, Taiwan
Department of Marine Leisure Management, National Kaohsiung University of Science and Technology, No. 142, Haijhuan Rd., Kaohsiung 81157, Taiwan
The Center for Water Resources Studies, National Sun Yat-sen University, No. 70, Lienhai Rd., Kaohsiung 80424, Taiwan
References (86)
Show source-provided references
1. (2021, December 01). Civil Aeronautics Administration of the Ministry of Transportation and Communications R.O.C. Annual Report 2020, Available online: www.motcmpb.gov.tw.
2. The Risk and Prevention of Ship Collision and Maritime Safety Management
3. MOTC (2021, June 24). Maritime Accident Case, Available online: stat.motc.gov.tw/mocdb/stmain.jsp?sys=100.
4. Factor and trend analysis of total-loss marine casualty using a fuzzy matter element method10.1016/j.ijdrr.2017.07.001 ↗
5. Statistical analysis of ship accidents and review of safety level10.1016/j.ssci.2016.02.001 ↗
6. Chae, C.J., Kim, K.H., and Kang, S.Y. (2021). Limiting Ship Accidents by Identifying Their Causes and Determining Barriers to Application of Preventive Measures. J. Mar. Sci. Eng., 9.10.3390/jmse9030302 ↗
7. Investigation of shipping accident injury severity and mortality10.1016/j.aap.2015.01.002 ↗
8. Kuznecovs, A., Ringsberg, J.W., Ullal, A.M., Bangera, P.J., and Johnson, E. (2022). Consequence analyses of collision-damaged ships—Damage stability, structural adequacy and oil spills. Ships Offshore Struct., 1–15.10.1080/17445302.2022.2071014 ↗
9. Study on collision avoidance in busy waterways by using AIS data10.1016/j.oceaneng.2010.01.012 ↗
10. Application of fuzzy bow-tie risk analysis to maritime transportation: The case of ship collision during the STS operation10.1016/j.oceaneng.2020.107960 ↗
11. Development of a quantitative risk assessment model for ship collisions in fairways10.1016/j.ssci.2016.07.018 ↗
12. A hybrid risk-based approach for maritime applications: The case of ballast tank maintenance10.1080/10807039.2017.1317204 ↗
13. A Big Data Analytics Method for the Evaluation of Ship—Ship Collision Risk reflecting Hydrometeorological Conditions10.1016/j.ress.2021.107674 ↗
14. Research on human factors cause chain of ship accidents based on multidimensional association rules10.1016/j.oceaneng.2020.107717 ↗
15. Human error contribution in collision and grounding of oil tankers10.1111/j.1539-6924.2010.01392.x ↗
16. Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters10.1016/j.ssci.2018.07.002 ↗
17. Human and organizational factors in maritime accidents: Analysis of collisions at sea using the HFACS10.1016/j.aap.2013.05.006 ↗
18. Event Tree Analysis of Marine Accidents in Bangladesh10.1016/j.proeng.2017.08.146 ↗
19. Formal Safety Assessment: A Critical Review
20. Safety in shipping: The human element10.1016/j.jsr.2006.04.007 ↗
21. Kristiansen, S. (2013). Maritime Transportation: Safety Management and Risk Analysis, Routledge.10.4324/978080473369 ↗
22. Xi, Y.T., Hu, S., Yang, Z.L., Fu, S.S., and Weng, J.X. (2022). Analysis of safety climate effect on individual safety consciousness creation and safety behaviour improvement in shipping operations. Marit. Policy Manag., 1–16.10.1080/03088839.2022.2059718 ↗
23. Collision risk assessment based on the vulnerability of marine accidents using fuzzy logic10.1016/j.ijnaoe.2020.06.005 ↗
24. A novel emergency decision-making model for collision accidents in the Yangtze River10.1016/j.oceaneng.2021.108622 ↗
25. An Analysis of The Key Human Factor in Collision Accident on Maritime Casualty—Application Analytic Hierarchy Process
26. Modified human factor analysis and classification system for passenger vessel accidents (HFACS-PV)10.1016/j.oceaneng.2018.04.086 ↗
27. Utilisation of cognitive map in modelling human error in marine accident analysis and prevention10.1016/j.ssci.2014.05.004 ↗
28. An approach of identifying the common human and organizational factors (HOFs) among a group of marine accidents using GRA and HFACS-MA
29. Influence of ship design and operational factors on human performance and evaluation of effects and sensitivity using risk models10.1016/j.oceaneng.2019.05.001 ↗
30. Robust breast cancer prediction system based on rough set theory at National Cancer Institute of Egypt10.1016/j.cmpb.2017.10.016 ↗
31. R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification10.1016/j.artmed.2021.102049 ↗
32. Missing traffic data imputation considering approximate intervals: A hybrid structure integrating adaptive network-based inference and fuzzy rough set10.1016/j.physa.2021.125776 ↗
33. Auto loan fraud detection using dominance-based rough set approach versus machine learning methods10.1016/j.eswa.2020.113740 ↗
34. Quantitative assessment of seismic risk in hydraulic fracturing areas based on rough set and Bayesian network: A case analysis of Changning shale gas development block in Yibin City, Sichuan Province, China10.1016/j.petrol.2020.108226 ↗
35. Single-parameter decision-theoretic rough set10.1016/j.ins.2020.05.124 ↗
36. Fault and event-tree techniques in occupational health-safety systems—Part i: Integrated risk-evaluation scheme10.30638/eemj.2014.232 ↗
37. Application of STPA on small drone operations: A benchmarking approach10.1016/j.proeng.2017.03.091 ↗
38. Human Error Bowtie Analysis to Enhance Patient Safety in Radiation Oncology10.1016/j.prro.2019.06.022 ↗
39. A risk analysis model for underground gas storage well integrity failure10.1016/j.jlp.2019.103951 ↗
40. A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory10.1016/j.ress.2021.107791 ↗
41. Putting on a bowtie to sort out who does what and why in the complex arena of marine policy and management10.1016/j.scitotenv.2018.08.168 ↗
42. From free-text to structured safety management: Introduction of a semi-automated classification method of railway hazard reports to elements on a bow-tie diagram10.1016/j.ssci.2018.03.011 ↗
43. Assessment of Technical Airworthiness in Military Aviation: Implementation and Further Advancement of the Bow-tie Model10.1016/j.proeng.2014.09.110 ↗
44. Risk assessment of ship anchorage handling operations using the fuzzy bow-tie method10.1016/j.oceaneng.2021.109500 ↗
45. Domínguez, R., Gomez, C., and Cerezo, O. (2021). International Conference on Applied Human Factors and Ergonomics, Springer.
46. Risk analysis for confined space accidents onboard ship using fuzzy bow-tie methodology10.1016/j.oceaneng.2022.112386 ↗
47. Organisational support and safety management: A study of shipboard safety supervision, The Economic and Labour Relations Review10.1177/1035304619869575 ↗
48. ISM Code implementation: An investigation of safety issues in the shipping industry10.1007/s13437-018-0153-4 ↗
49. MOTC (2019). Shipwreck Disaster Prevention and Rescue Business Plan.
50. Incorporation of human factors into ship collision risk models focusing on human centred design aspects10.1016/j.ress.2016.08.007 ↗
51. Impact of Technology on Safety as Viewed by Ship Operators10.7225/toms.v07.n01.005 ↗
52. A socio-technical approach of risk management applied to collisions involving fishing vessels10.1016/j.ssci.2006.01.002 ↗
53. Marine oil spill pollution causes and governance: A case study of Sanchi tanker collision and explosion10.1016/j.jclepro.2020.122978 ↗
54. The European Marine Safety Agency (EMSA) (2023, February 16). Annual Overview of Marine Casualties and Incidents. Available online: www.emsa.europa.eu/newsroom/latest-news/item/4867-annual-overview-of-marine-casualties-and-incidents-2021.html.
55. Chai, T., and Xue, H. (2021). A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method. PLoS ONE, 16.10.1371/journal.pone.0250948 ↗
56. Exploring shipping accident contributory factors using association rules
57. Validation of risk analysis for ship collision in narrow waters by using fuzzy Bayesian networks approach10.1016/j.oceaneng.2021.108973 ↗
58. Rough Sets10.1007/BF01001956 ↗
59. Local logical disjunction double-quantitative rough sets10.1016/j.ins.2019.05.033 ↗
60. Analysis by data mining in the emergency medicine triage database at a Taiwanese regional hospital10.1016/j.eswa.2011.02.152 ↗
61. User perspective of age-friendly transportation: A case study of Taipei City10.1016/j.tranpol.2014.08.010 ↗
62. Multi-criteria decision approach and sustainable territorial subsystems: An Italian rural and mountain area case study10.1016/j.landusepol.2017.09.052 ↗
63. The Bowtie method in safety management system: A literature review
64. Organizing learning processes on risks by using the bow-tie representation10.1016/j.jhazmat.2005.07.018 ↗
65. Bow-tie diagrams in downstream hazard identification and risk assessment10.1002/prs.11576 ↗
66. The science-policy interface of risk-based freshwater and marine management systems: From concepts to practical tools10.1016/j.jenvman.2018.08.053 ↗
67. Risk assessment for deep sea mining: An overview of risk10.1016/j.marpol.2019.02.056 ↗
68. Reducing maritime accidents in ships by tackling human error: A bibliometric review and research agenda10.1186/s41072-021-00098-y ↗
69. Information environment, fatigue, and culture in the maritime domain10.1177/1557234X11410391 ↗
70. Zhao, X.Y., He, Y.X., Huang, L.W., Mou, J.M., Zhang, K., and Liu, X. (2022). Intelligent Collision Avoidance Method for Ships ased on COLRGEs and Improved Velocity Obstacle Algorithm. Appl. Sci., 12.10.3390/app12188926 ↗
71. A Decision-Making Method for Ship Collision Avoidance Based on Improved Cultural Particle Swarm10.1155/2021/8898507 ↗
72. The contribution of risk management in ship management: The case of ship collision10.1016/j.ssci.2013.11.004 ↗
73. Shen, J.H., Liu, C.P., Chang, K.Y., and Chen, Y.W. (2021). Ship Deficiency Data of Port State Control to Identify Hidden Risk of Target Ship. J. Mar. Sci. Eng., 9.10.3390/jmse9101120 ↗
74. Mišković, D., Ivče, R., Hess, M., and Koboević, Ž. (2022). The Influence of Shipboard Safety Factors on Quality of Safety Supervision: Croatian Seafarer’s Attitudes. J. Mar. Sci. Eng., 10.10.3390/jmse10091265 ↗
75. Fuzzy domain and meta-heuristic algorithm-based collision avoidance control for ships: Experimental validation in virtual and real environment10.1016/j.oceaneng.2020.108502 ↗
76. Automatic collision avoidance of multiple ships based on deep Q-learning10.1016/j.apor.2019.02.020 ↗
77. The impacts of risk level based on PSC inspection deficiencies on ship accident consequences10.1016/j.rtbm.2020.100464 ↗
78. IMO resolution, A. (2011). 1052. Procedures for Port State Control, International Maritime Organization.
79. (2023, March 15). Paris MoU on Port State Control, White, Grey and Black List. Available online: www.parismou.org/detentions-banning/white-grey-and-black-list.
80. (2023, March 19). Tokyo MoU, Black–Grey–White Lists. Available online: www.tokyo-mou.org.
81. Safety first: Reconstructing the concept of seaworthiness under the maritime labour convention 200610.1016/j.marpol.2016.01.031 ↗
82. Integration of individual encounter information into causation probability modelling of ship collision accidents10.1016/j.ssci.2019.08.008 ↗
83. Review and analysis of methods for assessing maritime waterway risk based on non-accident critical events detected from AIS data10.1016/j.ress.2020.106933 ↗
84. A novel framework for regional collision risk identification based on AIS data10.1016/j.apor.2019.05.020 ↗
85. Evaluate VTS benefits: A case study of Zhoushan Port
86. A Study on the Risk Analysis based on the Trajectory of Fishing Vessels in the VTS Area