Abstract
AbstractIn this article, the problem of imprecision in assessing the performance of Safety Instrumented Systems (SIS) using fuzzy Markov chains is adressed. The scalar elementary probabilities usually considered in Markov chains are replaced by fuzzy numbers. It allows experts to express their uncertainty concerning the basic parameters of systems (common cause factors, failure rate …) and, to evaluate the impact of the uncertainty. We show how the imprecision induces significant changes on the Safety Integrity Level (SIL) of a SIS. The proposed method ensures the relevance of the results. It is affirmed by the comparison with results obtained by a Monte Carlo sampling approach.
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