Risk assessment is the heart of ISO and OHSAS auditions and also is vital demand for any industry to characterize hazards and their risks for personnel, environment and loss of money. Traditionally, Risk matrix was a very useful tool to estimate the risk of process or equipment or acts that helps decision-making processes. Establishment and development of soft set theory and its applications are used in recent years and are extended in combined forecasting, decision-making, information science and so on. Fuzzy modeling is one of the most powerful tools to estimate relation between input-output of nonlinear systems. In this method, fuzzy numbers are referred to variables that express uncertainties. A fuzzy number expresses relation between an imprecise or uncertain number, X and a membership function, ì that is between (0,1). In other words, the fuzzy logic tool provides a technique to deal with imprecision and information, the fuzzy theory provides a mechanism for representing linguistic constructs such as “many”, “low”, “medium”, “few”, etc. In the new view of analysts and decision makers, risk analysis is being done with great uncertainties because risk assessment requires detail information about damage frequency rate of particular processes and equipment components. This data usually are imprecise and uncertain. One of the advantages of fuzzy logic in the field of risk assessment is dealing with these problems.
Keywords: Fuzzy Logic, Risk Assessment, Uncertainties
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