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Complexity: Application to human performance modeling and HRA for dynamic environments

机译:复杂性:应用于人类性能建模和HRA的动态环境

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Although the argument has been made quite strongly and perhaps convincingly that advanced, highly automated control rooms consisting of advanced digital information and control systems will be simpler to operate and maintain; the case can be made that this potential benefit will only be true to the extent that we successfully control the amount of complexity present for the operating crew. Borrowing from complexity theory and human reliability analysis literature, we review the aspects of complexity that should be considered, discuss the implications, and review the extent to which we find current human reliability analysis (HRA) methods sensitivity to complexity in advanced digital environments. Next, we identify 3 complexity factors related to human performance and propose a rating scale approach that allows the analyst to more clearly allocate complexity levels for HRA purposes. These factor scores are used to form the basis of a composite complexity score (CCS) that can be used to support HRA. Although one method, the Simplified Plant Analysis Risk Model Human Reliability Analysis (SPAR-H), is selected for purposes of mapping the 3 complexity elements, the results are thought to support the qualitative and quantitative portions of most HRA methods
机译:虽然这一论点已经非常强烈,也许令人信服地令人信服,由先进的数字信息和控制系统组成的先进,高度自动化的控制室将更简单地运营和维护;可以使这种情况下,这种潜在的益处只会符合我们成功控制运营人员的复杂性的程度。从复杂性理论和人力可靠性分析文献中借用,我们审查了应考虑的复杂性的方面,讨论了这些影响,并审查了我们发现当前人类可靠性分析(HRA)方法对高级数字环境复杂性的敏感性的程度。接下来,我们确定与人类绩效相关的3个复杂性因素,并提出评级规模方法,允许分析师更明确地分配HRA目的的复杂程度。这些因子分数用于形成可用于支持HRA的复合复杂性得分(CCS)的基础。虽然一种方法,简化的工厂分析风险模型人可靠性分析(SPAR-H)是为了映射3个复杂性元素而选择,但结果被认为支持大多数HRA方法的定性和定量部分

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