Abstract
This paper proposes an index ‘likelihood of failure’ expressed by a fuzzy set instead of failure rate used in the conventional fault tree analysis, and presents a method of fault tree analysis based on fuzzy theory.
Likelihood of failure is the grade of failure caused by a component, human error or environment. A causal relation of common mode failure is expressed in a fault tree by a fuzzy relation. We define operations corresponding to AND, OR and IMPLICATION based on triangular norm or conorm in order to analyze the fault tree. And we present four criteria to evaluate the result of the present analysis. The first is the numerical likelihood of failure which gives the greatest grade of the membership of the fuzzy set. The second is defined as the potentiality of failure. The third is defined as the fuzziness of the first criterion. The last is interpreted as the importance of a basic event.
As an illustrative example, a circuit diagram of a power supply in a nuclear power plant is shown and its fault tree is analyzed, where the top event is a loss of electrical power supply to engineering safety features. It is shown that the present method well gives us the fuzziness of likelihood of failure and the potentiality of failure.
