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研究生: 林聖哲
Lin, Sheng-Che
論文名稱: 以虛擬電路填充最佳化積體電路佈局之方法
IC layout optimization by dummy filling methods
指導教授: 陳飛龍
Chen, Fei-Long
口試委員:
學位類別: 博士
Doctor
系所名稱: 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 110
中文關鍵詞: 化學機械研磨毫秒快速高溫熱退火虛擬電路填充基因演算法模擬退火法可製造性設計線性規劃
外文關鍵詞: Chemical Mechanical Polising, Milli-Second Anneal, Dummy Filling, Genetic Algorithm, Simulated Annealing, Design for Manufacturability, Linear Programming
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  • 降低製造的變異,提升良率是製造的目標,以往縮小製造變異的方法主要來自綿密的檢驗和統計製程管制,在製程或機台發生問題之前或問題之初期就能察覺,進行機台狀態維修或停機,讓問題不要繼續擴大。但進入奈米世代,許多製程對積體電路佈局的敏感度越來越顯著,製程的變異比例也隨著線寬的縮小而提高,許多與電路佈局設計相關的問題已經無法用傳統的檢驗和管制來解決,必須追本溯源到電路佈局設計來做改變與配合以提升其可製造性,這就是為何可製造性設計(Design for manufacturability)近來非常受到半導體產業界的重視。
    化學機械研磨的平坦度和電路佈局(circuit layout)密度的均勻度有高度相關,虛擬電路填充在空曠區以增加整體佈局密度的均勻度證實是可行方法,且有許多填充最佳化的方法已經提出,但目前方法的目標函數對多功能的測試晶片(Combo-chips)並不適用,本研究提出以最小變異數法來最佳化多功能的測試晶片的佈局密度之均勻度以提升其可製造性。此外,毫秒快速高溫退火製程和電路佈局局部的吸收率息息相關,而局部的吸收率則和材質的組合相關,本研究提出針對毫秒高溫退火製程提出虛擬電路填充最佳化方法。
    本研究分別探討化學機械研磨和毫秒高溫退火的虛擬電路填充最佳化,再以兩階段共同最佳化的方法探討化學機械研磨和毫秒高溫退火的虛擬電路填充的共同最佳化以及流程的整合。從實例驗證的結果發現本研究所提出之虛擬電路填最佳化之方法能有效提升佈局密度均勻度與表面吸收率的均勻度以提昇佈局設計在化學機械研磨和毫秒高溫退火製程的可製造性。


    目錄 IV LIST OF FIGURES VII LIST OF TABLES IX 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機 2 1.3 研究目的 5 1.4 研究大綱 7 第二章 文獻探討 10 2.1 半導體製程與良率 10 2.1.1半導體製程簡介 10 2.1.2半導體製程與良率的關係 12 2.2 電路佈局與半導體製程 13 2.3 設計之可製造性(design for manufacturability, DFM) 16 2.4化學機械研磨的探討 18 2.4.1 平坦化的目的 18 2.4.2化學機械研磨的運作原理 20 2.4.3化學機械研磨製程之問題 23 2.4.4以虛擬電路填充提升化學機械研磨的均勻度 24 2.5 毫秒快速高溫退火(Millisecond Anneal)製程 28 2.5.1 毫秒快速高溫退火的問題 28 2.5.2 表面吸收率與溫度均勻度之關係模式 30 2.6 基因演算法與模擬退火法的應用 31 2.6.1 基因演算法 31 2.6.2 模擬退火法 35 第三章 研究方法論 40 3.1研究架構 40 3.2 IC電路佈局分析 43 3.2.1 IC佈局的密度與可填充區域分析 43 3.2.2平均密度與等效密度的計算 45 3.3 化學機械研磨的虛擬填充最佳化問題定義 47 3.3.1 化學機械研磨的厚度模式與等效密度 48 3.3.2最小差距法(Minimum-Range)的研究 49 3.3.4 Target-based啟發法解最小變異法最佳化問題 55 3.4 快速高溫退火製程之虛擬電路填充問題 56 3.4.1 快速高溫退火溫度梯度模式與等效吸收率 56 3.4.2 快速高溫退火製程之虛擬電路填充最佳化 58 3.5 化學機械研磨與毫秒高溫退火製程虛擬填充共同最佳化 61 3.5.1 多目標規劃方法 61 3.5.2 兩階段共同最佳化 62 3.6啟發式的求解方法: 基因演算法(Genetic algorithm) 64 3.6.1 填充樣式的編碼 64 3.6.2 適應函數(Fitness function) 65 3.6.3 選取運算子(Selection operator) 65 3.6.3 交配運算子(Crossover operator) 66 3.6.4 突變運算子(Mutation operator) 67 3.7啟發式的求解方法: 模擬退火法(Simulated Annealing) 69 第四章 實例驗證與結果分析 70 4.1 化學機械研磨虛擬電路填充最佳化實作 70 4.2 化學機械研磨虛擬電路填充最佳化的結果分析 72 4.3 毫秒高溫退火虛擬電路填充最佳化實作 79 4.3.1 基因演算法(Genetic Algorithm)的實作 79 4.3.2 模擬退火法(Simulated Algorithm)的實作 82 4.3.3 實例驗證與結果分析 84 4.4 化學機械研磨與毫秒高溫退火兩階段共同最佳化實作 91 4.4.1 兩階段共同最佳化的實作 91 4.4.2實例驗證與結果分析 91 4.5 虛擬電路填充最佳化流程 94 第五章 結論與建議 96 5.1 研究結論 96 5.2 研究建議 99 參考文獻 101

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