HFACS-GMI的适用性和实用性

T. Joe-asare, E. Stemn, N. Amegbey
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引用次数: 1

摘要

为了在安全文献中提供事故原因及其对加纳采矿业的影响等信息,研究了安全文献中事故分析的分类方案。人因分析与分类方案(HFACS)应运而生,适用于事件分析。基于它适合于加纳采矿业(GMI)内的事件分析,提出了HFACS的衍生品,即HFACS-GMI。本研究旨在探讨HFACS-GMI的有用性和适用性。总共从加纳的一个露天金矿获得了56份事故调查报告,并使用HFACS-GMI进行了分析。以一起设备损坏事故和一起伤害事故为例,论证了编码处理在识别事故原因中的应用。分析显示,大多数事故与不利的工作场所/操作条件有关(151篇参考文献),其中物理环境(72.2%)被认为是该等级下的主要因果代码。在因果代码下,管理决策是造成事故的主要因素(74.1%)。大多数案件归因于错误(57.4%),其次是违反与运营商行为等级的既定规则和程序(51.1%)。在操作流程和领导缺陷原因代码下,工作标准不充分(27.8%)和未能确保胜任能力(24.1%)分别被认为是引用最多的纳米代码。管理决策在事故中起着至关重要的作用,在制定事故预防策略时应予以高度重视。研究表明,HFACS-GMI在矿山事故分析中是非常有用和适用的,并建议对矿山间的因果因素进行研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applicability and Usefulness of the HFACS-GMI
To present information such as causes of accidents and their consequences on the Ghanaian mining industry in the safety literature, classification schemes for incident analysis within the safety literature were studied. Human Factor Analysis and Classification Scheme (HFACS) emerged suitable for incident analysis. Base on its suitability for incident analysis within the Ghanaian Mining Industry (GMI), a derivative of the HFACS, namely HFACS-GMI, was proposed. This research seeks to study the usefulness and the applicability of the HFACS-GMI. Collectively, 56 incident investigation reports were obtained from an open cast gold mine in Ghana and analysed using the HFACS-GMI. Two cases, an equipment damage incident and an injury incident, were used to demonstrate the coding processing in identifying the causal factors. The analysis shows that most mishaps are associated with adverse workplace/operator conditions (151 references), with the physical environment (72.2%) being cited as the major causal code under the tier. Management decision showed a major contribution (74.1%) to mishap under the causal codes. Most cases were attributed to mistake error (57.4%) followed by the contravention (51.1%) of set rules and procedures with the operator's act tiers. Inadequate work standards (27.8%) and failure to ensure competency (24.1%) under the operational process and leadership flaw causal codes, respectively, were identified as the most cited nanocode. Management decision is critical in a mishap and should be given much attention in developing accident prevention strategies. The study has demonstrated that HFACS-GMI is very useful and applicable for incident analysis within the mining industry and is recommended to study causal factors across the mines.
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