keywords: Asset management, equipment, fuzzy logic, maintenance, risk priority number
In asset management, failure mode and effects analysis together with maintenance cost play a key role in determining a proper maintenance policy on equipment. In this work, a methodology is developed that aids decision making process in selected equipment using fuzzy logic inference engine of MATLAB. A maintenance cost model was developed to determine the best maintenance policy on each component of the equipment. The maintenance cost and the risk priority number variable were deployed as the input to the framework to determine the maintenance decisions. The proposed framework was applied to three pumps in the production plant of iron ore concentrates in National Iron Ore Mining Company, Itakpe to illustrate its applicability and efficiency. Results showed that the bearing components of the pumps were of the highest risk numbers at 927, 801 and 809 while the shaft components had the most delicate decision indices of 0.785, 0.798 and 0.510. The technique demonstrated in this research can be applied to pumps used in engineering industries.
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