Analysis of a 2-phase model for optimization of condition-monitoring intervals

Abstract

Condition monitoring is a maintenance strategy where decisions are made depending on either continuously or regularly measured equipment states. It reduces uncertainty with respect to actual states of equipment, and can thus avoid unnecessary repair or replacement. However, it involves capital expenditure and/or operational costs to perform measurements. This paper presents a basic model for the economic evaluation and optimization of the interval between successive condition measurements (also called inspections), where measurements are expensive and cannot be made continuously. It assumes that the technique can detect an intermediate state to failure for a failure mode of interest. The influence of competing risks is analyzed, leading to the conclusion that once the cost-effectiveness of the condition-monitoring has been established, competing risks need not be considered in determining the optimum condition monitoring interval. Inspection is cost-effective if the intermediate state has a: (1) nondecreasing hazard rate, and (2) shorter mean residence time than the good state (good-as-new condition), while costs of failure are high enough compared with inspection and repair costs in the intermediate state. Assuming that the distribution of the residence time in the second state is unimodal, estimation of the mean (or scale parameter) and standard deviation of this state, in many cases, provides enough information to make a good decision on the inspection interval. The most important model parameters are identified by sensitivity analyses; it is shown that the model can be simplified without seriously affecting optimal decision making. >