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研究生: 李育瑾
Lee, Yu-Chin
論文名稱: 扇出型晶圓級封裝製程之非線性翹曲分析與製程模擬器建立
Nonlinear Warpage Analyses and Development of Process Emulator for Fan-out Wafer Level Packaging
指導教授: 陳國聲
Chen, Kuo-Shen
共同指導教授: 李森墉
Lee, Sen-Yung
學位類別: 碩士
Master
系所名稱: 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 216
中文關鍵詞: 扇出型晶圓級封裝有限元素分析晶圓翹曲幾何非線性分析
外文關鍵詞: Asymmetric warpage, Fan-out wafer level package (FOWLP), Bifurcation, Finite element simulation
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  • 扇出型晶圓級封裝製程(FOWLP)具有成本低、高I/O接點數與更加的異質整合特性等優勢,因此廣泛運用於現今的封裝系統中。在製程中會經過一系列溫度循環與製程步驟,結構間的CTE不匹配會因溫差而產生翹曲,若材料選擇不當或是晶圓布局對稱性較低則容易發生非線性的翹曲,過大的翹曲則會降低產品良率。而針對此製程缺陷也有需多應用數值模擬之相關研究用以優化整體製程與材料參數組合。但大多數值模型結構詳細而複雜,若進行製程模擬有著極高的計算與時間成本。由此,本研究建立半解析模型針對非對稱翹曲的分歧點與翹曲幅度進行快速有效的預測,且在預測精準度方面半解析模型較尚未修正的解析模型精準度至多提升近兩倍,而為了更詳細觀察製程中各步驟的翹曲演變,本研究透過數值分析方法針對FOWLP中常見的chip first 與chip last製程建立製程模擬器,首先透過等效雙層結構的數值模型可在簡單的模型架構下可將各種晶圓布局與各參數的影響納入考慮,除了數值模型的有良好的泛用性之外,基於等效雙層結構模型所建立的製程模擬器在預測結果可接受的誤差範圍內得以大幅降低分析所耗費的時間,若將基於等效雙層結構模型所建的製程模擬器與以完整模型所建之製程模擬器相比,至少可節省十多倍的分析時間,最終綜合半解析模型與數值模型的預測結果根據影響翹曲的關鍵參數進行靈敏度分析,並提出翹曲防治的建議,本研究亦提出決策輔助判斷流程,透過有系統的參數探討可在新製程導入前評估各參數對於翹曲的影響力,防止大幅度的翹曲發生。綜上所述,藉由本研究所提出的製程模擬器與歸納出的關鍵參數,可對降低FOWLP製程中所產生的翹曲有所幫助,未來此研究成果也可拓展至其他封裝系統中,增進產業應用的實務價值。

    Fan-out wafer level package (FOWLP) are widely used in IC packaging industry, however the asymmetric warpage in the process may affect final yield and reliability of products. Traditionally, full-scale finite element simulations are usually used for warpage and stress prediction in IC packaging, but its case-by-case nature and high computational effort are not suitable for early design stage. In this work, the semi-analytical models for predicting bifurcation and warpage are proposed as cost-effective approaches for evaluating asymmetric warping. On the other hand, for observing warpage and stress in each process step, the process emulators based on equivalent bi-layer structures FE models are developed as a quick and effective way to evaluate the effect of each factor to induce wafer warpage. To identify key parameter for reducing wafer warpage, semi-analytical models and process emulators are used for material and process parameters optimization for improving processing reliabilities. Finally, the flow of this work could also be applied to other advanced packaging process.

    摘要 I ABSTRACT II EXTENDED ABSTRACT III 致謝 XXIX 目錄 XXXI 表目錄 XXXVIII 圖目錄 XL 符號及縮寫表 LI 第一章 緒論 1 1.1前言 1 1.1.2 扇出型晶圓級封裝製程介紹 2 1.1.3 晶圓翹曲介紹 3 1.2 文獻回顧 5 1.2.1 相關實驗文獻 5 1.2.2 晶圓翹曲預測解析模型 6 1.2.3 基於有限元素分析的封裝製程模擬 7 1.2.4 實驗室相關研究 9 1.2.5 文獻評論 9 1.3研究動機與目的 11 1.4研究方法 12 1.5本文架構 14 第二章 研究背景 16 2.1本章介紹 16 2.2扇出型晶圓級封裝 17 2.2.1 chip first 製程 18 2.2.2 chip last 製程 21 2.3 封膠材料性質 23 2.4晶圓翹曲 30 2.5晶圓翹曲之力學行為 34 2.5.1 線性解 34 2.5.2 幾何非線性 35 2.6文獻評論 43 2.7本章總結 46 第三章 研究方法總論 47 3.1本章介紹 47 3.2 研究主題 48 3.2.1 半解析模型 48 3.2.2 模型驗證 50 3.2.3製程模擬器 51 3.3 數值模型建立 52 3.3.1 完整結構模型 52 3.3.2 雙層結構模型 54 3.3.3 1/4完整模型 55 3.5研究流程 58 3.6本章總結 59 第四章 半解析模型之建立 60 4.1本章介紹 60 4.2 分歧點預測模型的發展 61 4.2.1模型修正 63 4.2.2 轉換因子的建立 69 4.3翹曲預測模型的發展 75 4.3.1 模型修正 76 4.3.2 封膠Tg因素的影響 80 4.4 討論 85 4.5 本章總結 87 第五章 實驗與數值模型驗證 88 5.1本章介紹 88 5.2試片製作 90 5.3 試片翹曲量測 93 5.4 數值模型建立 96 5.4.1數值模型與材料性質 96 5.4.2試片製作製程模擬 97 5.4.3試片量測製程模擬 99 5.5 數值模擬結果 100 5.6討論 102 5.6.1封膠楊氏係數誤差分析 102 5.6.2封膠CTE誤差分析 104 5.6.3封膠黏彈特性的影響 107 5.6.4 翹曲預測模型、數值模擬與試片實驗比較 111 5.7 本章總結 114 第六章 FOWLP製程模擬器之建立 115 6.1本章介紹 115 6.2數值模型的建立 116 6.3 材料性質的介紹 118 6.4製程所涉的分析種類 120 6.5製程模擬器展示 123 6.5.1整體製程模擬結果 123 6.5.2 post mold cure step 中的數值分析 125 6.5.3 製程模擬中等效雙層模型與1/4 模型比較 127 6.6 討論 129 6.7本章總結 132 第七章 製程模擬器於實際案例之應用 133 7.1本章介紹 133 7.2 CHIP FIRST 製程 134 7.2.1 chip first製程模擬器所用之數值模型與材料參數 134 7.2.2 以不同數值模型進行chip first製程模擬結果比較 139 7.3 CHIP LAST 製程 143 7.3.1 chip last製程模擬器所用之數值模型與材料參數 143 7.3.2 以不同數值模型進行chip last製程模擬結果比較 146 7.4 討論 151 7.5 本章總結 154 第八章 扇出型晶圓級封裝製程之參數分析 155 8.1本章介紹 155 8.2 參數分析規劃 156 8.3 材料參數分析 157 8.4 晶圓布局與幾何參數分析 161 8.5 製程參數分析 167 8.6討論 169 8.7 本章總結 174 第九章 研究結果與討論 175 9.1 全文歸納 175 9.2研究結果討論 178 9.2.1半解析模型性能評估 178 9.2.2製程模擬器分析結果 179 9.2.3 FOWLP之參數分析 182 9.2.4本文結果於工程應用與建議 183 9.3展望與未來工作 185 9.4本章總結 187 第十章 結論與未來展望 188 10.1本文結論 188 10.2 本文貢獻 190 10.3 未來工作 192 參考文獻 193 附錄A1 200 附錄A2 201 附錄B1 204

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