A fuzzy and Bayesian network CREAM model for human reliability analysis - The case of tanker shipping
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhou, Qingji | - |
dc.contributor.author | Wong, Yiik Diew | - |
dc.contributor.author | Loh, Hui Shan | - |
dc.contributor.author | Yuen, Kum Fai | - |
dc.date.available | 2019-03-07T04:39:15Z | - |
dc.date.issued | 2018-06 | - |
dc.identifier.issn | 0925-7535 | - |
dc.identifier.issn | 1879-1042 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/2079 | - |
dc.description.abstract | This paper proposes a quantitative human reliability analysis (HRA) model based on fuzzy logic theory, Bayesian network, and cognitive reliability & error analysis method (CREAM) for the tanker shipping industry. The common performance conditions (CPCs) in conventional CREAM approach are custom-modified to better capture the salient aspects of the situations and conditions for on-board tanker work. Fuzzy logic technique using triangle and trapezoidal membership functions is applied to model the uncertainty and ambiguity of the CPCs as well the control modes in CREAM. A Bayesian network reasoning model using the membership of CPCs as inputs is developed which determines the probability distribution of the control modes. Human error probability (HEP) is obtained from memberships of the control modes and the results of Bayesian network reasoning. A case study in tanker shipping industry with 18 crew members is provided, and the results show that the evaluation of HEP according to the proposed HRA model is very promising and the HRA model is consistent with the original CREAM approach. The sensitivity of the model is also checked against the inputs of the crew members. It is concluded that the enhanced HRA model is able to provide reliable human performance failure results. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.title | A fuzzy and Bayesian network CREAM model for human reliability analysis - The case of tanker shipping | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.ssci.2018.02.011 | - |
dc.identifier.bibliographicCitation | SAFETY SCIENCE, v.105, pp 149 - 157 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000428823800015 | - |
dc.identifier.scopusid | 2-s2.0-85042180207 | - |
dc.citation.endPage | 157 | - |
dc.citation.startPage | 149 | - |
dc.citation.title | SAFETY SCIENCE | - |
dc.citation.volume | 105 | - |
dc.type.docType | Article | - |
dc.publisher.location | 네델란드 | - |
dc.subject.keywordAuthor | Human reliability analysis | - |
dc.subject.keywordAuthor | CREAM | - |
dc.subject.keywordAuthor | Fuzzy logic theory | - |
dc.subject.keywordAuthor | Bayesian network | - |
dc.subject.keywordAuthor | Human error probability | - |
dc.subject.keywordPlus | HUMAN ERROR-PROBABILITY | - |
dc.subject.keywordPlus | MARITIME TRANSPORTATION | - |
dc.subject.keywordPlus | FAILURE MODE | - |
dc.subject.keywordPlus | QUANTIFICATION | - |
dc.subject.keywordPlus | UNCERTAINTY | - |
dc.subject.keywordPlus | OPERATION | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.