TY - JOUR
T1 - Review of techniques and challenges of human and organizational factors analysis in maritime transportation
AU - Wu, Bing
AU - Yip, Tsz Leung
AU - Yan, Xinping
AU - Guedes Soares, C.
N1 - Funding Information:
The research presented in this paper was sponsored by a grant from International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 51920105014 ), National Natural Science Foundation of China (Grant No. 52071248 and 51809206 ), Hubei Natural Science Foundation (Grant No. 2021CFB312 ), Fundamental Research Funds for the Central Universities ( WUT:2020Ⅲ041 , WUT:2021IVB066 ). This work contributes to the Strategic Research Plan of the Centre for Marine Technology and Ocean Engineering (CENTEC), which is financed by the Portuguese Foundation for Science and Technology (Fundação para a Ciência e Tecnologia - FCT) under contract UIDB/UIDP/00134/2020 .
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/3
Y1 - 2022/3
N2 - This paper summarises the advanced techniques adopted for the analysis of human and organizational factors, which are the predominant factors in maritime accidents, and the various attempts that have been made to reduce human errors by identifying the existing challenges. Advanced techniques for human and organizational factor modelling, including human error identification in accident investigation, human error probability quantification in risk analysis, and human and organizational factor analysis for emergency situations, are comprehensively analysed and discussed. The most widely used modelling technique for human error identification is the Human Factors Analysis and Classification System (HFACS), and preconditions and unsafe acts exert the most important impacts on maritime accidents in previous studies. Moreover, Cognitive Reliability Error Analysis (CREAM) is the most widely used technique for human error probability quantification, and fuzzy, evidential reasoning and Bayesian networks are often incorporated for common performance condition (CPC) quantification and synthesis processes. In the future, other techniques should be introduced and developed for modelling HOFs for maritime transportation. Moreover, the challenges for human and organizational factors, including data collection, individual factors, and autonomous shipping, are identified for future studies. Consequently, this paper provides insight into human and organizational factors for maritime transportation, including quantification modelling, solutions to data collection and future research directions.
AB - This paper summarises the advanced techniques adopted for the analysis of human and organizational factors, which are the predominant factors in maritime accidents, and the various attempts that have been made to reduce human errors by identifying the existing challenges. Advanced techniques for human and organizational factor modelling, including human error identification in accident investigation, human error probability quantification in risk analysis, and human and organizational factor analysis for emergency situations, are comprehensively analysed and discussed. The most widely used modelling technique for human error identification is the Human Factors Analysis and Classification System (HFACS), and preconditions and unsafe acts exert the most important impacts on maritime accidents in previous studies. Moreover, Cognitive Reliability Error Analysis (CREAM) is the most widely used technique for human error probability quantification, and fuzzy, evidential reasoning and Bayesian networks are often incorporated for common performance condition (CPC) quantification and synthesis processes. In the future, other techniques should be introduced and developed for modelling HOFs for maritime transportation. Moreover, the challenges for human and organizational factors, including data collection, individual factors, and autonomous shipping, are identified for future studies. Consequently, this paper provides insight into human and organizational factors for maritime transportation, including quantification modelling, solutions to data collection and future research directions.
KW - Challenges for future
KW - Human and organizational factors
KW - Human error probability quantification
KW - Identification techniques
KW - Maritime transportation
UR - http://www.scopus.com/inward/record.url?scp=85120491281&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2021.108249
DO - 10.1016/j.ress.2021.108249
M3 - Review article
AN - SCOPUS:85120491281
SN - 0951-8320
VL - 219
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 108249
ER -