University-Industry Graduate Research Assistantships for Developing Analytical Models to Estimate Performance Measures and Optimize Resource Allocation in a Complex Server Manufact

这项研究计划下的大学-工业合作研究计划在数学科学（UICRP）的目的是开发分析模型，以估计一个复杂的服务器制造系统的性能指标。服务器制造系统将被建模为一个网络的队列和性能指标将估计使用参数分解。还将建立一个模拟模型，以估计业绩计量。将比较分析模型和模拟模型之间的误差，以确定拟议分析模型的准确性。精确的分析模型可以消除开发仿真模型的需要。性能度量估计可以与容量规划公式一起使用，以优化组装/测试阶段的资源数量。因此，可以最小化完成订单所需的时间，可以提高整个设施的各种资源的利用率，并且可以避免由于错过最后期限而导致的成本。在大学和行业研究人员的共同指导下，研究生将开发模型和解决方案方法，这将使服务器制造商和其他类似服务器制造的应用程序受益。

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.