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，我们认为， 建模和误差控制是该战略的重要组成部分 以提高结构的可靠性。 的目的 研究的目的是开发一种实用的方法来预测 结构工程中的人为错误。 这涉及 估计结构对总危险的敏感性 设计、施工和使用中的错误。 人为错误会影响 由一系列的条件构成的人类，经济， 社会和政治气候影响着每一个项目。 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）。 一定程度的风险 与这种敏感性有关。 不同程度的 风险和结构背景要求采取不同的风险战略 管理 另一个目标是制定一个风险管理 以应急计划的形式减少风险的程序 这是对粗差敏感性的结果。 敏感性分析是 有效的工具扩展到控制一些可预测的错误。 敏感性分析将扩大到包括适当的成本- 分配方案的效益分析。 这项工作是基于 先前研究的结果（NSF资助MSM-8304962）和 美国国家科学基金会人为错误建模研讨会（6月， 1986年）。

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).