Enhancing the FMEA technique using a combination of Expectation interval, TAGUCHI, MOORA, and geometric mean methods

Risk assessment is a critical component of any maintenance system since the risk of most engineering systems has to be established in order to identify the appropriate maintenance strategy for maintaining it. A commonly used tool in the industry is the Failure Mode and Effect Analysis (FMEA). However, the conventional FMEA makes use of precise information from experts in determining the risk of failure modes, which many experts are averse to, because of the difficulty in determining an exact risk value for the failure mode. The use of an alternative approach that allows the utilisation of both precise and imprecise information becomes imperative. In this paper, two novel risk prioritisation techniques, MOORA-RPN and geometric mean-RPN, are developed for risk prioritisation of failure modes involving imprecise information from experts. Both methods use an expectation interval technique in converting imprecise experts rating into minimum and maximum interval values, while utilising the Taguchi method to produce a different combination of decision criteria minimum and maximum risk values. The MOORA-RPN and geometric mean- RPN use MOORA and geometric mean methods, respectively, for the ranking of the risk of failure modes. The risk prioritisation techniques proposed are compared with a technique in the literature, using a case study of a fuel oil system of a marine diesel engine. The results showed that the proposed techniques with lesser computational effort produce results similar to the mathematical technique in the literature.