首页> 外文学位 >Human error in mining: A multivariable analysis of mining accidents/incidents in Queensland, Australia and the United States of America using the human factors analysis and classification system framework.
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Human error in mining: A multivariable analysis of mining accidents/incidents in Queensland, Australia and the United States of America using the human factors analysis and classification system framework.

机译:采矿中的人为错误:使用人为因素分析和分类系统框架对昆士兰州,澳大利亚和美利坚合众国的采矿事故/事故进行多变量分析。

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摘要

Historically, mining has been viewed as an inherently high-risk industry. Nevertheless, the introduction of new technology and a heightened concern for safety has yielded marked reductions in accident and injury rates over the last several decades. In an effort to further reduce these rates, the human factors associated with incidents/accidents need to be addressed. A modified version of the Human Factors Classification and Analysis System (HFCAS-MI) was used to analyze lost time accidents and high-potential incidents from across Queensland, Australia and fatal accidents from the United States of America (USA) to identify human factor trends and system deficiencies within mining. An analysis of the data revealed that skill-based errors (referred to as routine disruption errors by industry) were the most common unsafe act and showed no significant differences between accident types. Findings for unsafe acts were consistent across the time period examined. The percentages of cases associated with preconditions were also not significantly different between accident types.;Higher tiers of HFACS-MI were associated with a significantly higher percentage of fatal accidents than non-fatal accidents. These results suggest that there are differences in the underlying causal factors between fatal and non-fatal accidents. By illuminating human causal factors in a systematic fashion, this study has provided mine safety professionals the information necessary to reduce mine accidents/incidents further.
机译:从历史上看,采矿一直被视为固有的高风险行业。然而,在过去的几十年中,新技术的引入和对安全性的高度关注已导致事故和伤害率的显着降低。为了进一步降低这些比率,需要解决与事件/事故相关的人为因素。人为因素分类和分析系统(HFCAS-MI)的修改版用于分析澳大利亚昆士兰州的误工事故和高危事件以及美利坚合众国(USA)的致命事故,以识别人为因素趋势和采矿中的系统缺陷。对数据的分析表明,基于技能的错误(按行业称为常规中断错误)是最常见的不安全行为,并且显示事故类型之间没有显着差异。在整个检查期间内,发现不安全行为的结果是一致的。在不同事故类型之间,与前提条件相关的病例百分比也没有显着差异。较高级别的HFACS-MI与致命事故相比,致命事故百分比显着高于非致命事故。这些结果表明,致命和非致命事故之间的潜在因果因素有所不同。通过系统地阐明人为因素,这项研究为矿山安全专业人士提供了进一步减少矿难/事故所必需的信息。

著录项

  • 作者

    Patterson, Jessica Marrie.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:15

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