clustering of condition-based maintenance considering perfect and imperfect actions

Recent developments in condition monitoring technology have delivered important opportunities for condition-based maintenance. although condition-based maintenance allows for more effectively planned maintenance actions, its relative performance depends on the behavior of the deterioration process. the objective of this paper is to develop a clustering model of maintenance activities and analyze the effect of perfect, imperfect, and hybrid maintenance on the cost. we consider a two-component system that experiences three degradation states before a complete failure. the components are equipped with a monitoring system that signals before each state change, on which our clustering is based. actually, we have three types of clustering aiming at cost minimization. the results provide a general insight into when and how the activities are clustered and what kind of maintenance is selected such that the cost is minimized. moreover, the results showed that clustering with a more degree of the clusters is more appropriate and produced cost savings about 70%, if the fixed cost exceeds a certain amount.