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  • 學位論文

群組演算法於晶圓製造廠設施規劃之應用

Application of Clustering Algorithm to the Facility Planning of Wafer Fabrication

指導教授 : 陳建良

摘要


晶圓製造廠的設施規劃對於工廠整體的營運績效具有重要性的影響,良好的設施設計可減少晶圓平均搬運距離、增加製程設備使用率並提升工廠的競爭力。本研究提出一套群組演算法,規劃與評估出晶圓製造廠初始設計方案。透過分析晶圓製程步驟,將各個製程層所使用的製程設備指派於同一生產區,依據相關績效的評估,將鄰近生產區進行結合以改善績效,包括生產區效率、機台數、機台使用率、平均搬運距離和混合績效等績效評估指標。依據晶圓製造廠實際資料,以單產品和多產品實際案例進行方法的建構,並利用實驗設計評估群組演算法的效益。實驗結果顯示群組演算法所發展之設施佈置方案,可以改善傳統晶圓廠設施規劃方案績效,尤其在晶圓平均搬運距離的績效上,可提供管理者作為決策參考之依據。

並列摘要


Facility planning is crucial to the performance of wafer fabs in semiconductor industry. This research proposes a clustering algorithm to develop and evaluate initial fab design alternatives. Clustering algorithm analyzes and allocates the tools for processing steps of each layer into a bay. With respect to the performance measures of efficiency of bays, the required number of machines, utilization of machine, average moving distance and a mixed performance, it then combines adjacent bays to improve the performance. A case study with single and multiple products using data from real fabs was conducted and the design of experiments was used to evaluate the effectiveness of the clustering algorithm. Simulation results show that, compared to traditional layout alternatives, the proposed clustering algorithm can improve the fab performance, especially in terms of average wafer moving distance.

參考文獻


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