Application of Data-Mining and FMEA Techniques in Maintenance System to Improve Equipment Performance

This study utilized the CMMS database that was reserved maintenance activities work order. Data-mining was applied to discover of knowledge that was hidden in the CMMS database, such as important repair activities and critical equipments. The failure modes and effects analysis (FMEA) was applied to analyze the risks of equipment. There are three indices of FMEA in this work: the occurrence (O) that can be learned from the Number of failures in CMMS database; the likelihood of being detected (D) that refers to the difficulty of detection and severity (S) that can be quantified from the Production stop and the Production of unfit product. The fuzzy analytic hierarchy process (FAHP) was applied to determine the relative weightings of four factors, then a equipment risk priority number (E-RPN) can be calculated for each one of the equipment. Numerical results indicated that through the use of the proposed approach, the rate of the equipments performance can be improved while the E-RPN is above 7.

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