This research initiative under the University-Industry Cooperative Research Programs in the Mathematical Sciences (UICRP) is aimed to develop analytical models to estimate the performance measures of a complex server manufacturing system. The server manufacturing system will be modeled as a network of queues and the performance measures will be estimated using parametric decomposition. A simulation model will also be developed to estimate the performance measures. The error between the analytical and simulation models will be compared to determine the accuracy of the proposed analytical models. An accurate analytical model can eliminate the need to develop simulation models. The performance measure estimates can be used with a capacity planning formulation to optimize the number of resources at the assembly / test stages. Consequently, the time required to fill an order can be minimized, the utilization of the various resources across the facility can be improved, and cost due to missed deadlines can be avoided. Jointly mentored by the university and industry researchers, the graduate students will develop the models and solution approaches which will benefit server manufacturers and other applications which resemble server manufacturing.