Study on diagnosis error assessment of operators in nuclear power plants

Abstract

The purpose of this study is to suggest a framework to assess diagnosis error of operators in nuclear power plants. In nuclear power plants, human error caused by inappropriate performance due to inadequate diagnosis of situation by operators have been considered to be critical since it may lead serious problems. In order to identify and estimate the human errors, various human error analysis methods were developed so far. Most human error analysis methods estimate diagnosis error through time reliability curve or expert judgments. In this study, a new framework to assess diagnosis error was suggested. It is assumed that diagnosis error is caused by inadequate quality of data and diagnosis error can be observed by using information processing model of human operators. Based on this assumption, we derived the assessment items for the quality of data and diagnosis error taxonomy here. © 2014 Springer International Publishing.