Causality diagram using normal fuzzy numbers

This paper applies fuzzy concepts to causality diagram, where the probabilities of all events are considered as fuzzy numbers, and shows that n-ary fuzzy AND and OR operators are used to evaluate the possibility of system events failure. A normal fuzzy number (NFN) can be defined completely by a triplet (m, α, β). We can diagnose system fault based on fuzzy probability of the events. The goal of this paper is to replace probabilistic considerations in the causality diagram by the probabilistic ones and to reduce the difficulty arising from the inexact and insufficient information of the distribution functions of basic event and linkage event. The result of numerical simulating is coincident with the fact, so the fuzzy causality diagram is effective. The research indicates that fuzzy causality diagram is so effective in fault analysis, and it is more flexible and adaptive than conventional causality diagram.