| 研究生: |
吳盛治 Wu, Sheng-Chih |
|---|---|
| 論文名稱: |
以田口法應用雷射切割參數最佳化之探討 Study of the optimization parameter of laser grooving |
| 指導教授: |
趙隆山
Chao, Long-Sun |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 工程科學系碩士在職專班 Department of Engineering Science (on the job class) |
| 論文出版年: | 2019 |
| 畢業學年度: | 107 |
| 語文別: | 中文 |
| 論文頁數: | 58 |
| 中文關鍵詞: | 田口法 、Low-K 、COG 、雷射開槽製程 |
| 外文關鍵詞: | wafer, Taguchi method, low-K, COG, laser grooving |
| 相關次數: | 點閱:160 下載:16 |
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本研究以介紹雷射參數與雷射基本原理,藉由基本的簡介以了解雷射目前的發展與目前實際運用上有什麼貢獻與使用。雷射不只在生活上的使用,更有工業上,半導體業界,以及生活與軍事上的應用。此研究以介紹雷射切割在半導體封裝於雷射切割上的運用,晶圓使用雷射切割,不只使產量能夠明顯提升,晶圓雷射切割也能提升品質更加符合目前的生產水準,加入雷射切割也能提升後製程成品後的整體良率。
也隨著電子消費品的功能強大的設計與輕薄短小體積,像是在生活所用到的3C產品、消費性產品:如手機、手持式的3C配戴商品或其他業界上的使用。晶圓逐漸在電晶體結構製程中加入金屬層與銅導線,並採用Low-K低介電層與銅導線等技術也逐漸成為目前趨勢。然而,因晶圓增加銅導線製程,隨著晶圓製程的提升也增加晶圓切割的難度,低介電層(Low-K)與銅製程晶圓,使得切割品質與良率的下降,也會有晶粒正面崩缺與Peeling 破裂的問題出現。故加入雷射切割來改善此問題,也使得切割製程進一步的提升品質與產品的可作業性,並且加入田口實驗設計法取得最佳的雷射切割參數,使得製程評估更有信心水準。
This thesis introduces the principle of laser grooving and laser related information, and introduces the process of laser grooving into the semiconductor packaging process. The semiconductor processes are wafer fabrication, wafer testing, wafer processing, wafer testing, and output. This research is mainly to introduce the laser grooving into the traditional packaging, so that the die has an additional layer of protection during the post-processing, which can greatly reduce the probability of defective products, and protect the die in the processing of diamond blade saw processing. Therefore, the laser grooving is a very important part of the semiconductor packaging.
In the study, the experimental instruments are the instruments produced online, including wafer grinder, laser grooving machine, die saw, die strength tester, precision microscopy and SEM.
The experimental method is to bring the Taguchi method (TM) into the optimization of the laser cutting process. Taguchi method is by means of experimentation to obtain the optimized combination of process parameters, and is a quality engineering method for efficiently introducing new products and improving processes. The method mainly uses the orthogonal table and signal noise ratio as an analysis tool, emphasizes the need to consider quality issues when designing new product processes, and tries to optimize when new products are introduced. In the study, the DOE factor method mentioned in the Taguchi method and the selection of control factors are used to optimize the quality of the wafer after laser grooving.
In the laser grooving, different working parameters and material properties will make the results different. After the defect items of the wafer cutting are actually confirmed, the laser grooving is introduced and the Taguchi method is utilized to optimize the results of laser grooving. The depth after laser cutting can also produce the difference in wafer strength. After determining the depth of the metal layer to be removed, the Taguchi method is applied to the working parameters optimization. In the Taguchi analysis, the reaction diagram of each factor and their variation are explored, the optimal parameter combination is selected and verified by experiments.
Therefore, after with parameter optimization to find the most appropriate ideal parameters, and then draw the reaction diagram of each factor. With the variation and further analysis, the optimal combination of parameters after optimization was selected and verified by experiments to confirm that the quality results are consistent the theoretical prediction.
In this study, there are still some uncompleted improvements, and the following points are proposed as a reference for the subsequent research:
1. According to the study, using the L18 mixed level orthogonal table as the factor configuration, whether more factors can be added to use the full factor analysis. Although it takes more resources and time, it may be able to improve the quality level.
2. This study uses wafer cleaning speed, laser power, laser pass rate times, moving speed, and laser pulse frequency, and other five parameters for the experimental control factor combined with the Taguchi experimental design method to optimize the process parameters. In the future, it can be further confirmed by combining different solving methods and different experimental design methods. It can be also extended to other process improvements, which can reduce unnecessary costs caused by employing the trial and error method to optimize parameters.
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