Modeling and Control of Human Errors Using Expert Systems

人为错误是结构失效的主要原因。因此，误差的建模和控制是提高结构可靠性策略的重要组成部分。这项研究的目的是开发一种实用的方法来预测结构工程中人为错误发生的可能性。这涉及评估结构对设计、施工和使用中的严重错误危险的敏感度。人为错误受到许多条件的影响，这些条件构成了影响每个单独项目的人类、经济、社会和政治气候。这些气候条件及其与误差的关系构成了基于知识的专家系统(KBES)的数据。一定程度的风险与这种敏感度有关。不同的风险水平和结构背景要求采取不同的风险管理战略。另一个目标是以应急计划的形式制定风险管理程序，以减轻严重错误敏感性所带来的风险。灵敏度分析是控制某些可预测误差的有效工具。敏感度分析将扩大到包括对分配备选办法进行适当的成本效益分析。这项工作是基于先前一项研究的结果(美国国家科学基金会资助MSM-8304962)和美国国家科学基金会人为错误建模研讨会(1986年6月)的建议。

Human error is the major cause of structural failure. Therefore, modeling and control of errors are an important part of the strategy to improve the reliability of structures. The objective of this study is to develop a practical method to predict the likelihood of occurrence of human error in structural engineering. This involves estimating the sensitivity of the structure to the hazard of gross errors in design, construction and use. Human errors are influenced by a number of conditions which constitute the human, economical, social and political climate influencing each individual project. These climatic conditions and their relations to errors constitutes the data of a knowledge-based expert system (KBES). A level of risk is associated with this measure of sensitivity. Different levels of risk and structural context call for different strategies for risk management. Another objective is to develop a risk management procedure in the form of a contingency plan to mitigate the risk entailed by the gross error sensitivity. Sensitivity analysis is an effective tool extended to control some of the predictable errors. Sensitivity analysis would be extended to include a proper cost- benefit analysis of allocation options. The work is based on the results of a previous study (NSF grant MSM-8304962) and the recommendations of NSF Workshop on Modeling Human Errors (June, 1986).