An analysis of human-error factors using Fuzzy Integral-Measure model and natural languages

Abstract

This paper is concerned with a fuzzy model of human error and error factors (PSF: Performance Shaping Factor). We propose an analytical method identifying relations between human error factors and degree of importance of them through the model. In order to treat mutual relationship between human error factors, we introduce the concept of Fuzzy Integral and Fuzzy Measure and use the natural language for estimation of PSF which is needed for identification of Fuzzy Measure. We extend this method by use of Extension Principle in order to treat a fuzzy set. As a case study, we analyze human error factors (PSF) concerning robot stoppage and check the validity of our analytical method.