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Human Error Analysis Technique and Its Application to Marine Accidents

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dc.contributor.author나성-
dc.contributor.author김홍태-
dc.contributor.author김혜진-
dc.contributor.author하욱현-
dc.date.accessioned2021-08-03T05:44:13Z-
dc.date.available2021-08-03T05:44:13Z-
dc.date.issued2010-03-31-
dc.identifier.urihttps://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/1181-
dc.description.abstractThe management of safety at sea is based on a set of internationally accepted regulations and codes, governing or guiding the design and operation of ships. The regulations most directly concerned with human safety and protection of the environment are, in general, agreed internationally through the International Maritime Organization(IMO). IMO has continuously dealt with safety problems and, recognized that the human element is a key factor in both safety and pollution prevention issues(IMO, 2010). This paper proposes a human error analysis methodology which is based on the human error taxonomy and theories (SHELL model, GEMS model and etc.) that were discussed in the IMO guidelines for the investigation of human factors in marine casualties and incidents. In this paper, a cognitive process model, a human error analysis technique and a marine accident causal chains focused on human factors are discussed, and towing vessel collision accidents are analyzed as a case study in order to examine the applicability of the human error analysis technique to marine accidents. Also human errors related to those towing vessel collision accidents and their underlying factors are discussed in detail.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisher한국항해항만학회-
dc.titleHuman Error Analysis Technique and Its Application to Marine Accidents-
dc.title.alternative해양사고 인적과실 분석기법 활용-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.bibliographicCitation한국항해항만학회지, v.34, no.2, pp 145 - 152-
dc.citation.title한국항해항만학회지-
dc.citation.volume34-
dc.citation.number2-
dc.citation.startPage145-
dc.citation.endPage152-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorhuman element-
dc.subject.keywordAuthorhuman error analysis-
dc.subject.keywordAuthorSHELL model-
dc.subject.keywordAuthorcognitive process model-
dc.subject.keywordAuthorGEMS model-
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