半導體製造工業一個資本與技術密集的產業，隨著特徵尺寸的縮小及晶圓半徑的增加，為了提升產出良率以及增加設備效率，精密的控制方法就顯得有其必要。
在本研究中我們將半導體製造程序視為多階段多M/M/1/K機台的等候網路，各類不同產品在每一階段中可依指定比例分配派送至各機台中處理，而每一機台的製程配方依EWMA控制策略逐批調整。根據這些假設我們發展出混整數非線性規劃模型來決定可達成最大化製程能力以及最小化系統時間的最佳化派遣策略，並成功的利用數值模擬方法驗證此派遣模式的合理性。我們也在不同案例研究中討論輸入產品及機台干擾對輸出產品品質的效應，並且建議應避免的控制器調整參數範圍，同時也探討了不同操作參數影響系統時間的效應，結果顯示平均抵達速率、流失機率上限及排隊容量除了影響平均系統時間也影響流失機率。

Semiconductor manufacturing industry is a capital and technology-intensive industry. As feature sizes shrink and wafer sizes increase, intricate control methods are needed to improve the product quality and tools utilization of any production process.
In this thesis, the semiconductor manufacturing process is treated as multiple M/M/1/K queuing systems operated in a network, and different products can be routed to tools in each stage. It is assumed that the exponentially-weighed-moving- average (EWMA) controller is implemented in each tool to adjust the process recipe from run to run. Based on these assumptions, a mixed integer nonlinear programming model (MINLP) is formulated to determine the optimal dispatching (routing) policies for maximizing process capability or minimizing average system time. Numerical simulation procedure is also devised to confirm the validity of the resulting dispatching model. The simulation results show that the predictions of this model are reasonable. Moreover, the impacts of changing noises of product and tool for product quality are investigated in case studies and the safe range of parameters values are suggested in the thesis. The impacts of changing parameters values for operating efficiency are also investigated. Both the expected system time and also the loss probability can be shown to be dependent upon average arrival rate, loss probability limit and queueing capability.

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