The Army is currently in the midst of a recapitalization (RECAP) program that calls for the rebuilding and selective upgrading of 17 systems. Because this program's plans for the scale, scope, and type of RECAP for each of these systems have been evolving over time, the program may benefit from additional information about the relationships between Army vehicle ages and operating costs and the practical implications of those relationships. In this study, we analyzed the effects of vehicle age and other factors (such as usage, initial odometer reading, and location) on repair costs and availability and embedded our results in a spreadsheet-based vehicle replacement model used to estimate optimal replacement or RECAP age for a specific model fleet. Our regression analyses showed that age and usage are significant predictors of HMMWV repair costs and downtime when odometer reading, location, and variant (HMMWV type) are controlled for. More specifically, repair costs and downtime increase with age, the increase tapering off for older vehicles. Additionally, the effects of usage on repair costs and downtime were found to be positive but weaker than the effects of age. Although the regression equations only explained a small percentage of the variance in maintenance costs for individual vehicles, sensitivity analyses indicated that the equations yielded good predictions of average vehicle costs by age group (for a given location and usage level), as well as aggregate repair costs at the battalion and brigade levels.
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