Since the beginning of project management, people have been asked to perform "more with less" in expeditious time while attempting to balance the inevitable challenge of the time/cost tradeoff. This is especially true within the Department of Defense today in prosecuting the Global War on Terrorism both in Afghanistan and Iraq. An unprecedented and consistent level of Operational Tempo has generated heavy demands on current equipment and has subsequently forced the need to recapitalize several legacy systems until suitable replacements can be implemented. This paper targets the UH-60A:A Recapitalization Program based at the Corpus Christi Army Depot in Corpus Christi, Texas. More specifically, we examine one of the nine existing project sub-networks within the UH-60A:A program, the structural/electrical upgrade phase. In crashing (i.e. adding manpower or labor hours) the network, we determine the minimal cost required to reduce the total completion time of the 68 activities within the network before a target completion time. A linear programming model is formulated and then solved for alternative scenarios. The first scenario is prescribed by the program manager and consists of simply hiring additional contractors to augment the existing personnel. The second and third scenarios consist of examining the effects of overtime, both in an aggressive situation (with limited longevity) and a more moderate situation (displaying greater sustainability over time). The initial linear programming model (Scenario 1) is crashed using estimates given from the program scheduler. The overtime models are crashed using reduced-time crash estimates. For Scenarios 2 and 3, the crashable times themselves are reduced by 50% and 75%, respectively. Initial results indicate that a completion time of 79.5 days is possible without crashing any activities in the network. The five-year historical average completion time is 156 days for this network. We continue to crash the network in each of the three scenarios and determine that the absolute shortest feasible completion times, 73 days for Scenario 1, 76 days for Scenario 2, and 77.5 days for Scenario 3. We further examine the models to observe similarities and differences in which activities get targeted for crashing and how that reduction affects the critical path of the network. These results suggests an in-depth study of using linear programming and applying it to project networks to grant project managers more critical insight that may help them better achieve their respective objectives. This work may also be useful as the groundwork for further refinement and application for maintenance managers conducting day-to-day unit level maintenance operations.