Abstract
The successful implementation of a condition based predictive maintenance strategy for engineering equipment depends to a large extent in the very choice of such systems. CM systems have certain design parameters that suggest their ability to detect an onset of failure and predict the time of ultimate failure. It is obvious that a CM system with higher values of these parameters can deliver better results. However it is not only difficult to comprehensively quantify these parameters but also evaluate their utility in the overall operation and maintenance of equipment. In this paper a fuzzy inference system (FIS) based elicitation of these parameters has been proposed in a multi-objective optimisation framework using genetic algorithm. The results provide the maintenance decision maker with several options to choose from based on the overall objectives of the plant and install a suitable CM system.
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Verma, A.K., Srividya, A. & Ramesh, P.G. FIS based selection of CM system design parameters from a multi-objective optimisation model using GA. Int J Syst Assur Eng Manag 2, 14–20 (2011). https://doi.org/10.1007/s13198-011-0050-0
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DOI: https://doi.org/10.1007/s13198-011-0050-0