Fuzzy based risk prioritisation in an auto LPG dispensing station

Abstract A fuzzy rule based inference model assessing the failure modes for risk ranking in FMEA to manage risks and make maintenance decisions is applied to a LPG refuelling station in this paper. Normally in FMEA, risk priority number (RPN) is determined by multiplication of feature scores that are inferred from the degree or probability of occurrence, severity and non detection of the problem, without taking into consideration the relative importance of factors. In fuzzy approach, linguistic assessment of factors is evaluated to obtain risk priority number. A rule based fuzzy inference engine generates the priority ranks of identified failure modes. Direct evaluation is possible with the aid of grey theory by assigning weights to the features in the absence of expertise to develop an inference rule base. The GRA approaches can solve the problem of risk prioritising, which needs expertise to develop rule base while building the fuzzy inference system. By applying fuzzy FMEA and fuzzy logic with grey relational approach (GRA), expert linguistic opinions are used to rank the identified failure modes and the results are presented. The risk of the failure modes are ranked in an inclusive approach based on the fuzzy domain projections. It is effective and feasible to handle various types of uncertainties, such as incompleteness, fuzziness, imprecision, and so on, in the risk analysis process.