Journal of Systems Engineering and Electronics ›› 2011, Vol. 33 ›› Issue (12): 2782-2787.doi: 10.3969/j.issn.1001-506X.2011.12.38

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蒋英杰, 孙志强, 宫二玲, 谢红卫   

  1. 国防科学技术大学机电工程与自动化学院, 湖南 长沙 410073
  • 出版日期:2011-12-19 发布日期:2010-01-03

Method for correlation analysis between scenario and human error

JIANG Ying-jie, SUN Zhi-qiang, GONG Er-ling, XIE Hong-wei   

  1. College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, China
  • Online:2011-12-19 Published:2010-01-03


提出了一种分析情景环境与人为差错之间对应关系的方法。将情景环境分为操作者、机器、任务、组织、环境和辅助系统6个方面,建立了包含38个元素的行为形成因子分类方法,为人为差错成因的查找提供了参考模板。在SRK(skill-based, rule-based and knowledge-based)模型的基础上引入疏忽/遗忘/错误分类框架,将人为差错分为技能型疏忽、技能型遗忘、规则型疏忽、规则型错误以及知识型错误等5种基本的人为差错类型。使用灰色关联分析方法,从“结果原因”和“原因结果”两个方向分析行为形成因子与人为差错类型之间的关联关系。通过分析可以得到,与特定人为差错类型相关的各种行为形成因子的排序以及特定行为形成因子所可能诱发的各种人为差错类型的排序。通过示例分析表明,该方法是一种分析情景环境与人为差错之间对应关系的有效方法,可以为人为差错的预测和预防提供重要的指导。


A new method is proposed to analyze the correlation between scenario and human error. The scenario is decomposed into six aspects, which are operator, machine, task, organization, environment and assistant devices. Based on the scenario decomposition, a taxonomy of performance shaping factor is constructed, which includes thirty-eight items and can provide a reference template for the investigation of human error causes. Based on the skill-based, rule-based and knowledge-based (SRK) model, the slip/lapse/mistake framework is introduced to classify human errors, which are categorized as skill-based slip and lapse, rule-based slip and mistake, and knowledge-based mistake. Grey relational analysis is introduced to analyze the correlation between performance shaping factors and human error types, in which the correlations of “consequent-antecedent” and “antecedent-consequent” are both analyzed. By this method, performance shaping factors related to some specified human error type and human error types caused by some specified performance shaping factor both can be sorted according to their correlation degrees. A case study is provided, which shows that the proposed method is applicable in analyzing the correlation between scenario and human error, and can provide some important implications for human error prediction and human error reduction.