• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Safety science >Classification of human errors in grounding and collision accidents using the TRACEr taxonomy
【24h】

Classification of human errors in grounding and collision accidents using the TRACEr taxonomy

机译：使用TRACEr分类法对接地和碰撞事故中的人为错误进行分类

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper applies a Human Error Identification tool called Technique for the Retrospective and Predictive Analysis of Cognitive Errors to the analysis of ship accidents. Grounding and collision accidents investigation reports involving sixty-four vessels published by the UK's Maritime Accident Investigation Branch, the Transportation Safety Board of Canada and the National Transportation Safety board of the United States of America are coded and analysed using the taxonomy of the Technique for the Retrospective and Predictive Analysis of Cognitive Errors. A total of two hundred and eighty-nine errors performed by the operators are coded. The results of the codification process are analysed with the objective of identifying the main task errors, cognitive domains and the technical equipment involved in grounding and collision accidents and the factors that affect the performance of the operators. This identification is a necessary step towards safety improvements resulting from dealing with the identified problems. A discussion on the use of the taxonomy of the Technique for the Retrospective and Predictive Analysis of Cognitive Errors is provided and it is proposed to combine it with some elements of the CASMET approach to accident investigation so as to improve the applicability of the methodology to the analysis of ship accidents. (C) 2016 Elsevier Ltd. All rights reserved.
机译：本文将一种称为“技术”的人为错误识别工具用于认知错误的回顾性和预测性分析，用于船舶事故的分析。英国海事事故调查处，加拿大运输安全委员会和美利坚合众国国家运输安全委员会发布的涉及64艘船舶的着陆和碰撞事故调查报告均使用该技术的分类法进行了编码和分析。认知错误的回顾性和预测性分析。由操作员执行的总共289错误被编码。对编纂过程的结果进行分析，目的是确定与接地和碰撞事故有关的主要任务错误，认知领域和技术设备以及影响操作员性能的因素。这种识别是通过解决已识别的问题而改善安全性的必要步骤。讨论了使用技术分类法对认知错误进行回顾性和预测性分析，并建议将其与CASMET方法的某些要素结合起来用于事故调查，以提高该方法在故障诊断中的适用性。船舶事故分析。 （C）2016 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号