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研究生:林毓舜
研究生(外文):Yu-Shun Lin
論文名稱:隨機規劃法在半導體機台組態規劃之應用
論文名稱(外文):Application of Stochastic Programming to Tool Portfolio Planning In Semiconductor Manufacturing
指導教授:周雍強周雍強引用關係
指導教授(外文):Yon Chou
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:工業工程學研究所
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:96
中文關鍵詞:隨機規劃半導體製造產能規劃機台組態規劃
外文關鍵詞:semiconductor manufacturingstochastic programmingcapacity planningtool portfolio planning
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半導體製造的機台組態規劃是指依據產品需求與製程要求,考量投資報酬與風險等因素,以決定工廠內機台類別與數量的規劃程序,所面臨的困難主要在於產品需求不確定以及設備採購的前置時間很長。隨機規劃法是一種適用於不確定性問題的數學規劃法,其效益與不確定性的程度有關,本研究將評估隨機規劃法在機台組態決策的適用性,並證明該方法確有顯著效益。隨機規劃法還未為產業所普遍採用,本文建議在面對需求不確定的產業環境,晶圓製造廠非常值得採用這個方法。
另一方面,雖然隨機規劃法對需求預測偏誤有較高的容忍度,但也相對造成解空間複雜度的增加,透過本研究所提出如何選擇具代表性的樣本情境點及合宜的規劃視野亦能夠有效的縮減解空間,取代部分文獻是發展演算法改進求解效率的觀點,使此法應用於機台組態規劃上能更加的完備,進而創造社會經濟福祉。
Tool portfolio planning is an important task in semiconductor manufacturing in which the types and quantities of processing tools are determined. The challenging facing tool portfolio planning is the uncertainty in product demand and process technology. The paper is made up of two parts. Stochastic programming is a method that is suitable for problems with uncertain factors. However, its utility will depend on the level of uncertainty. We evaluate the economic benefits of using stochastic programming in this thesis. We show that the benefits are very significant and recommend that the method of stochastic programming should be used in tool portfolio planning in the semiconductor manufacturing industry.
Although the stochastic programming method has more tolerant of demand forecast inaccuracy, it causes to increase solution space complexity relatively. The core issues of this study how to select representative scenario outcomes and planning horizons will be reduce solution space efficiently in order to replace the viewpoint of developing algorithm.
第1章 緒論 1
1.1 問題背景與描述 2
1.1.1 半導體產能規劃的複雜性與困難性 2
1.1.2 不同視野規劃工作的項目 3
1.1.3 產能規劃決策程序與方法 3
1.2 研究目的 5
1.3 研究方法 5
1.4 論文架構 6
第2章 隨機規劃法簡介 7
2.1 機率空間與隨機變數 7
2.2 隨機規劃法之概念 8
2.3 階期(STAGE)與時程(TIME HORIZON) 9
2.4 二階隨機規劃法 9
2.5 多階隨機規劃法 13
2.6 相依模型(RECOURSE MODEL) 14
2.7 應用隨機規劃法於機台組態規劃 17
2.8 衡量指標 21
第3章 文獻回顧與探討 26
3.1 中長期產能規劃工作項目 26
3.2 需求情境(樹)分析與建模 30
3.2.1 二元樹模型 31
3.2.2 最小平方統計性質建構法 32
3.3 以隨機規劃為方法之產能規劃文獻探討 33
第4章 需求情境樹之建構法 36
4.1 機率分配的逼近 36
4.2 情境樹生成模型與程序 38
4.3 有效情境點數目的檢驗 42
第5章 規劃視野之影響 50
5.1 產能規劃建模 50
5.1.1 二階隨機規劃模型 51
5.1.2 資料來源分析 52
5.1.3 隨機規劃模型建構程序 52
5.2 規劃視野對其解影響的實驗設計 53
5.2.1 需求情境模型為幾何布朗運動 54
5.3 規劃視野結論與探討 64
第6章 結論與建議 68
6.1 結論與貢獻 68
6.2 未來研究建議 68
第7章 參考文獻 70
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23.Occhino, Thomas J., “Capacity Planning Model: The Important Inputs, Formulas, and Benefits,” 2000 IEEE/SEMI Advanced Semiconductor Manufacturing Conference, 2000.
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