A simulation-based decision support system for finite population maintenance logistics

This thesis presents a decision support system, MAINTAIN, that was developed to assist maintenance and logistics planners in the evaluation of alternative strategies that might be used in the maintenance of a finite population of end items. The modeled population must consist of a finite number of identical end items, each at age zero at the beginning of the analysis. End items are modeled at their component level, with the lifetime of each component described by a probability distribution. These components are assumed to fail independently of each other and to cause end item failure if any one component should fail. Several component-level preventive maintenance policies are integrated into the modeling system and include age-based replacement, opportunistic lookahead replacement, or no replacement until failure.

Also incorporated into the model is the use of two repair facilities, which function as constraints on the resources available to perform maintenance tasks. One repair facility is used under normal conditions, while the second can be used when the first facility is operating beyond its capacity.

MAINTAIN is a simulation-based modeling system, in that a proposed or actual maintenance system is captured as an input data set and its operation is simulated over the specified planning horizon. Time-series output statistics are produced by the model to allow the analysis of time dependent parameters such as population availability, maintenance costs, spares requirements and repair facility utilization. Output data are available in several forms for use in external analyses.