Enhancing the FMEA technique using a combination of Expectation interval, TAGUCHI, MOORA and Geometric mean methods
Risk assessment is a key component of any maintenance system since the risk of most engineering system 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 make 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 which allows the utilization of both precise and imprecise information becomes imperative. In this paper two novel risk prioritization techniques, MOORA-RPN and geometric mean-RPN are developed for risk prioritization 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, whilst utilizing Taguchi method to produce a different combination of decision criteria minimum and maximum risk values. The MOORA-RPN and geometric mean-RPN uses MOORA and geometric mean methods respectively for the ranking of the risk of failure modes. The risk prioritization techniques proposed are compared with a technique in 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 similar results with the mathematical technique in literature.