UDC 62.5 © Mangey Ram, Ritu Chandna FUZZY SYSTEM AVAILABILITY ANALYSIS WITH DIFFERENT MEMBERSHIP FUNCTIONS OF SYSTEM FAILURE MODE The analysis of system reliability often requires the use of vague and imprecise data, subjective-judgments, and approximate system models. <...> By allowing imprecision and approximate analysis fuzzy logic provides an effective tool for characterizing system reliability in these circumstances. <...> In practice, the failure rates and transition rates of repairable systems contain both randomness and fuzziness. <...> So it is appropriate to assume these rates of systems to be fuzzy random variables. <...> In this paper, authors incorporating the concepts of fuzzy logic, fuzzy inference system and linguistic variables to the calculate availability of the system. <...> Fuzzy inference system is developed in Matlab and relationships of availability with failure rates and transition rates are shown. <...> The main aim of the paper is to apply fuzzy set theoretic concepts in the multidisciplinary area of reliability. <...> INTRODUCTION The concept of fuzzy reliability has been introduced by a number of authors and the various forms of fuzzy reliability theory have been presented [2, 15, 20, 30]. <...> Their results show that all the fuzziness, coverage factor, and the maintenance have significant effects on the fuzzy reliability behavior of gracefully degradable computing systems. <...> In another work of Cai et al. [14] introduced the concept of profust reliability and a conceptual framework of profust reliability theory is developed on the basis of the fuzzy state assumption and the probability assumption. <...> They showed that the binary state assumption in probist (conventional) reliability theory is not extensively acceptable and thus system failure and success should be defined as fuzzy states such that the fuzzy state assumption has to be taken to replace the binary state assumptions. <...> Ramachandran et al. [31] developed fuzzy Markov modeling for a power generator with a derated state. <...> Kim et al. [7] developed a numerical stability analysis methodology for the singleton-type linguistic fuzzy logic controller (FLC). <...> Luo et al. [23] presented a hierarchical grey-fuzzy motion decisionmaking algorithm, which is capable of integrating multiple sequential data for decision making and for the design of the control kernel of the target tracking system which <...>