The purpose of this study is to examine the failure trend of HVAC systems in high-rise office buildings using the reliability assessment, and propose a method of predicting an optimal inspection period for condition-based preventive maintenance (CBM) using the Monte Carlo method, in point of view of randomness and independency between failure and inspection. This study describes the probability process method of measuring the effect of condition-based preventive maintenance on HVAC system's reliability and optimization of condition-based preventive maintenance. A simulation model is presented to analyze condition-based preventive maintenance through a fixed period maintenance inspection by maintenance personnel conducted to detect failure occurring. Based on this simulation model, the effects of condition-based preventive maintenance on units of HVAC system's reliability are quantitatively obtained, and the mean time between failures of units under CBM action is suggested. In addition, the basic characteristics of the condition-based preventive maintenance are analyzed by sensitivity analysis. As a result of this study, the method to predict an optimal inspection period is also suggested in order to increase the reliability of units, and effect on expected profit of optimal preventive maintenance inspection period is computed.
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