Error mode prediction.
Error mode prediction.
复制标题
错误模式预测。
作者：
E. Hollnagel;M. Kaarstad;H. C. Lee
对事故（“人为错误”）的研究主要是努力开发“错误”分类法和“错误”模型，以追溯可能的原因。然而，在人的可靠性分析（HRA）领域，有一个显着的实际需要的方法，可以预测发生错误的行动-定性和定量。本实验检验了一种基于认知可靠性和错误分析方法（CREAM）的定性绩效预测方法。对使用不同类型报警系统的操作员进行了可能的错误操作预测。这些数据是作为大规模实验的一部分收集的，实验使用的是全范围模拟器中的专业核电厂操作员。分析表明，预测在70%以上的情况下是正确的，而且预测的覆盖范围主要取决于前面的任务分析的全面性。
The study of accidents ('human errors') has been dominated by efforts to develop 'error' taxonomies and 'error' models that enable the retrospective identification of likely causes. In the field of Human Reliability Analysis (HRA) there is, however, a significant practical need for methods that can predict the occurrence of erroneous actions--qualitatively and quantitatively. The present experiment tested an approach for qualitative performance prediction based on the Cognitive Reliability and Error Analysis Method (CREAM). Predictions of possible erroneous actions were made for operators using different types of alarm systems. The data were collected as part of a large-scale experiment using professional nuclear power plant operators in a full scope simulator. The analysis showed that the predictions were correct in more than 70% of the cases, and also that the coverage of the predictions depended critically on the comprehensiveness of the preceding task analysis.