Fuzzy fault tree analysis

Reliability of products is frequently a prime safety consideration. Interpretation of reliability is both quantitative and qualitative. Extensive quantitative analysis employing probablistic risk assessment has been widely performed to provide predicted hazard or accident minimization. Weibull probability data and information is a vital tool of these quantitative risk assessments, but so are qualitative methods such as fault tree analysis. Qualitative aspects of product risk contribution are subjective and contain many uncertainties. Risk analysis with all the inherent uncertainties is a prime candidate for fuzzy logic application. Most risk analyses do not have a method of expressing, propagating, or interpreting uncertainty. A fuzzy logic method employing Weibulls to represent membership functions for a set of fuzzy values (and fuzzy intervals) has been developed. Mixtures of "crisp" values with less-certain values do not "spoil" the analysis. The method can address subjective, qualitative, and quantitative uncertainties involving risk analysis.<>