Risk Assessment of Maintenance activities using Fuzzy Logic

Abstract This paper presents a new model to quantify the risks associated with maintenance activities by coupling the risk analysis method with fuzzy logic. The goal is to calculate the qualitative values of the risk level. The quantification of the Risk Priority Number (RPN) is based on three parameters: frequency, detectability, and severity. However, its result is often subjective and does not present the exact value. In addition, the combinations of different scores related to the three aforementioned parameters may have the same value of RPN even when the importance of the risks is not the same; hence the utility of fuzzy logic. A model based on the fuzzy sets theory is proposed for assessing the risk level of maintenance failure scenarios in the LPG supply chain. Such approach allows choosing priority failures that affect equipment and the whole supply chain system.

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