Designing and implementation of a fuzzy-dynamic model to evaluate system’s risk and reliability

The purpose of this article is to permit the system safetyand reliability analysts to evaluate the criticality or risk associated withitem failure modes. the factors considered in traditional failure modeand effect analysis (fmea) for risk assessment are frequency of occurrence(o), severity (s) and detectability (d) of an item failure mode.because of the subjective, qualitative and dynamic nature of the informationand to make the analysis more consistent and logical, an approachusing fuzzy logic and system dynamics methodology is proposed.in the proposed approach, severity is replaced by dependency parameterthen, these parameters are represented as members of a fuzzy setfuzzified by using appropriate membership functions and are evaluatedin fuzzy inference engine, which makes use of well-defined rule base andfuzzy logic operations to determine the value of parameters related tosystem’s transfer functions. the fuzzy conclusion is then defuzzified toget transfer function for risk and failure rate. the applicability of theproposed approach is investigated with the help of an illustrative casestudy from the automotive industry. the results provide an alternatesolution to that obtained by the traditional method. the suggested assessmentmodel was developed using toolbox platform of matlab 6.5r.13.