The Development of an Analytic Method Evaluating Correlative Human Factors among Marine Casualties Using HFACS-MA Framework

碩士 === 國立臺灣海洋大學 === 商船學系 === 102 === According to the statistics of maritime accidents from 1987 to 2012 made by P &; I Club, human factors are the primary causes of the accidents. In order to prvent the similar maritime accidents from happening again, thoroughly analyzing the context of the acc...

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Bibliographic Details
Main Authors: Wang, Shou-Yan, 王授彥
Other Authors: Chen, Shih-Tzung
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/g2r3up
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Summary:碩士 === 國立臺灣海洋大學 === 商船學系 === 102 === According to the statistics of maritime accidents from 1987 to 2012 made by P &; I Club, human factors are the primary causes of the accidents. In order to prvent the similar maritime accidents from happening again, thoroughly analyzing the context of the accidents and identifying the latent conditions of the factors would be the key. Thus, the goal made by the IMO -- "The safer shipping, the cleaner ocean" could be achieved Therefore the present study proposes a novel analytic method using an updated human factors framework, which is a derivative of Human Factors Analysis and Classification System (HFACS) proposed by a previous research work according to the IMO guideline A.884(21) “Investigation of Human Factors in Marine Casualties and Incidents”, named as HFACS-MA ( for Marine Accidents). The updated HFACS-MA is modified and specified in this thesis, through literatures review and several real cases analyzed done by the present study in order to improve the classification accuracy of the human factors identified. Meanwhile, the proposed analytic method which combines Correspondence Analysis (CA) and Hierarchical Cluster Analysis (HCA) can also be deemed as a complement to pair the cases for further analysis among accidents concerned. Hence the correlative issue between accidents and human factors as well as the similarity issue among accidents can be solved more objectively. By analyzing eight marine accidents, this study has shown that the following outcomes can be gained while utilizing the proposed analytic method and the updated HFACS-MA framework. These outcomes are: (a) the classifications of human factors can be more accurate; (b) the relevance between human factors and the accidents can be clearer, including the similarities among cases; and (c) providing a more objective figure for pairing the cases for correlation analysis. Therefore, it is argued that the authority would get the benefits of figuring out the context and the latent conditions of an accident if the proposed method with the updated HFACS-MA framework is utilized. The benefits also include highlighting the more vulnerable parts of the system according to the human factors found form the accidents concerned.