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系統識別號 U0026-0812200915261013
論文名稱(中文) 以反應曲面法搭配基因演算法進行堆疊晶 QFN 構裝體疲勞壽命之最佳化設計
論文名稱(英文) Optimal Design of Fatigue Life for Stacked Die Quad Flat No Lead Package by Using Response Surface Method and Genetic Algorithm
校院名稱 成功大學
系所名稱(中) 工程科學系碩博士班
系所名稱(英) Department of Engineering Science
學年度 97
學期 2
出版年 98
研究生(中文) 方子睿
研究生(英文) Tzu-jui Fang
電子信箱 player2kimo@hotmail.com
學號 n9696120
學位類別 碩士
語文別 中文
論文頁數 146頁
口試委員 口試委員-吳文方
口試委員-光灼華
口試委員-賴新一
指導教授-陳榮盛
中文關鍵字 反應曲面法  基因演算法  Global/Local 分析法 
英文關鍵字 Response surface method  Genetic Algorithm  Global/Local method 
學科別分類
中文摘要 近年來,由於電子產品追求輕薄短小、低成本及優越的電性能和
熱性能,傳統之低腳數IC 漸漸被QFN IC 所取代。再者,3D 堆疊封
裝技術越來越受到重視。故本文將針對可攜式電子產品大量使用的
QFN 構裝體結合3D 堆疊封裝技術,進一步研究堆疊晶QFN 構裝體。
本文採用ANSYS10.0進行分析,並根據JEDEC規範將堆疊晶QFN構裝體施予-40°C~125°C的溫度循環負載。錫膏選用亞蘭德模型,然後使用有限區域收斂法搭配Global/Local分析法節省運算所需資源與時間,並且使用Coffin-Manson疲勞壽命公式來計算堆疊晶QFN構裝體的疲勞壽命,隨後,利用反應曲面法結合基因演算法進行最佳化分析,求得最佳參數組合,可有效地改善堆疊晶QFN構裝體之可靠度。
在進行最佳化之前,先以一次一因子法篩選可靠度較大的控制因
子,然後將可靠度較大之因子利用反應曲面法分析求得迴歸模型,最後,將所求得之迴歸模型利用基因演算法以全域式之搜尋方法,求得最佳化指標及最佳組合參數。
由一次一因子法和反應曲面法都顯示,較大的印刷電路板熱膨脹
係數、較小的印刷電路板楊氏模數、較大的封膠熱膨脹係數、較小的晶片墊熱膨脹係數、較薄的印刷電路板厚度及較小的晶片面積可有效地改善堆疊晶QFN 構裝體的疲勞壽命。最後,利用基因演算法演化後的最佳製程參數之構裝體疲勞壽命為6240 次,較原使製程提升約15 倍,因此有效改善堆疊晶QFN 構裝體之可靠度。
英文摘要 With the characters of light-weight, mini-size, low costs, and excellent electrical and thermal performances, the traditional low pin-count IC has been replaced by QFN IC in recent years. Furthermore, the 3D packaging technology facilitated to above purposes has been gradually noticed. By incorporating the 3D packaging technology with the quad flat lead-free package which is widely used in portable electronic products, this paper aims to further analyze the stacked die QFN package.
This paper adopts ANSYS10.0 software for analysis. Based on the JEDEC code, the stacked die QFN is subjected by a thermal cycle of -40℃~125℃. The material property of solder paste is assumed to be Anand’s model. Then the finite-regional convergence method and the Global/Local method are combined to save the resources and times in computing. The Coffin-Manson fatigue life formula is applied to predict the fatigue life of the solder paste in the stacked die QFN package. After that, the response surface method is combined with Genetic Algorithm to proceed optimization analysis and obtain the optimal parameter combination to improve the reliability of the stacked die QFN package.
Prior to the process of the optimal design on reliability of stacked die QFN package, the most significant factors are chosen by the one factor at a time design method and the experiment is planned by the response surface method to construct the regression model. Afterwards, the global search with Genetic Algorithm is applied to the regression model to obtain the optimization indicator and the optimal combination parameters.
Both the one factor at a time design method and the response surface method show that the solder fatigue life increases along with the reduction of the die size, thickness of PCB, Young's modulus of PCB, CTE of die pad as well as the increase of CTE of mold compound and CTE of PCB. Finally, the optimal design derived from the response surface method and Genetic Algorithm results in the fatigue life of 6240 cycles which shows a 15 times increase compared to the original design. Therefore the reliability of the stacked die QFN module package has been efficiently improved.
論文目次 中文摘要 ……………………………………………………………………………I
英文摘要 …………………………………………………………………………III
誌謝 ……………………………………………………………………………… V
目錄 ………………………………………………………………………………VII
表目錄 ……………………………………………………………………………XI
圖目錄 ……………………………………………………………………………XIII
符號說明 ………………………………………………………………………XVIII
第一章 緒論 ………………………………………………………………………1
1-1 前言 ………………………………………………………………………1
1-2 研究動機與目的 ………………………………………………………3
1-3 文獻回顧…………………………………………………………………5
1-4 研究方法 ………………………………………………………………10
1-5 章節提要 ………………………………………………………………11
第二章 理論基礎 ……………………………………………………………12
2-1研究主題…………………………………………………………………13
2-2亞蘭德黏塑性本構模型………………………………………………13
2-2-1亞蘭德黏塑性本構模型………………………………………13
2-2-2決定材料參數 …………………………………………………15
2-3有限區域之區域平均進行收斂分析 ……………………………16
2-4 Global/Submodel 分析法 …………………………………………17
2-5錫膏破壞模式 …………………………………………………………19
2-6疲勞機制…………………………………………………………………20
2-7反應曲面法………………………………………………………………24
2-7-1迴歸模型…………………………………………………………24
2-7-2迴歸因子實驗水準配置法……………………………………26
2-7-3迴歸模型的配適性 ……………………………………………27
2-8基因演算法(Genetic algorithm ,GA) ………………………………29
2-8-1基因演算法之源起 ……………………………………………29
2-8-2基因演算法之演化流程………………………………………30
第三章 全域/局部模型配合有限區域之平均等效應變收斂分析……42
3-1堆疊晶QFN構裝體分析模型………………………………………42
3-1-1堆疊晶QFN構裝體模型簡介………………………………42
3-1-2堆疊晶QFN構裝體整體(全域/局部)分析流程…………43
3-1-3堆疊晶QFN構裝體模型之基本假設條件 ………………43
3-2堆疊晶QFN構裝體全域模型之建立與收斂分析………………44
3-2-1堆疊晶QFN全域模型之建構 ………………………………44
3-2-2全域邊界條件 …………………………………………………45
3-2-3全域溫度負載 …………………………………………………45
3-2-4堆疊晶QFN全域模型之分析結果…………………………46
3-2-5堆疊晶QFN全域模型收斂分析……………………………46
3-3堆疊晶QFN構裝體局部模型之建立與收斂分析 ………………………47
3-3-1局部模型之範圍 ………………………………………………47
3-3-2局部模型邊界條件及溫度負載 ……………………………48
3-3-3局部模型含有限區域之範圍分析 …………………………48
3-3-4局部模型網格之收斂分析……………………………………49
3-4堆疊晶QFN構裝體模型之評估 …………………………………51
3-5全域精細模型與全域/局部模型之差異分析……………………53
3-5-1效能比較…………………………………………………………54
第四章 一次一因子設計法篩選控制因子 ………………………………82
4-1單一因子水準值之選擇………………………………………………82
4-2一次一因子檢驗法之分析結果 ……………………………………83
4-3單一因子分析結果探討………………………………………………89
第五章 反應曲面法進行最佳化設計分析…………………………………98
5-1反應曲面法實驗設計…………………………………………………98
5-2迴歸模型之建立與分析 ……………………………………………100
5-2-1實驗結果與計算反應曲面之指標 ………………………101
5-2-2決定模型形式 …………………………………………………101
5-2-3等效應變範圍指標(RI)之迴歸模型及變異分析 ………101
5-3以反應曲面法探討各因子間變化對可靠度之影響 …………103
5-3-1以反應曲面法與一次一因子法分析各因子變化對可靠度之比較 ………………………………………………………103
5-3-2以反應曲面法探討因子間交互變化對可靠度之影響106
5-3-3利用反應曲面法之迴歸模型建立基因演算法的適應度函數及最佳化…………………………………………………110
第六章 結論與未來研究方向 ……………………………………………136
6-1結論………………………………………………………………………136
6-2未來研究方向 …………………………………………………………139
參考文獻 …………………………………………………………………………141
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