現行的智慧手機在高屏幕面積占比率的競爭下，屏幕下指紋識解決方案已成為各手機大廠的賣點之一。如何在有限的手機屏幕下空間，放入更大且更薄的生物(指紋)識別元件將是各生物識別解決方案商設計上一大挑戰。 該論文研究的超聲波生物(指紋)識別元件TFT玻璃基板(500um)，須經化學蝕刻的薄化製程將原本厚度減至90um，相較一般傳統TFT面板玻璃基板薄化後厚度300um左右有極大的差異，且單片TFT基板上元件數量也較面板產品多(約500 chips)，因此對於薄化後玻璃厚度均勻極為要求，如厚度均勻度不佳時，將會造成後道玻璃切割/裂片作業時，導致切割深度差異，裂片後玻璃邊緣的崩損品質問題，同時對識別功能效益上也會有一定程度的影響。在超薄及厚度均勻度高規格要求條件下，對超聲波生物(指紋)識別元件TFT玻璃薄化製程將是一大考驗。
本論文研究方式是應用田口實驗設計方式(Taguchi Method)，改善方式是運用六標準差DMAIC系統流程，以清楚定義問題及問題的範圍，選出關鍵品質特性，並列出關鍵的製程輸出變數、衡量階段收集的資料，再應用田口實驗設計法規畫出最少的實驗組合，衡量重要因子及水準，找出最佳的薄化製程參數設定，再經由製程監控下確認改善方案有效性。
本研究利用「科學化-田口實驗設計」及「系統化-六標準差DMAIC」的問題分析手法，提升研究個案公司的問題解決能力，大幅度降低問題改善時間與實驗驗證成本。
關鍵字：田口實驗設計、六標準差DMAIC，蝕刻薄化，生物(指紋)識別

Nowadays, the increase in screen ration for smartphones has become one of the selling strategies for phone makers. Implementation of larger and thinner biometric (fingerprint) recognition component has become a challenge for biometric solution providers. This paper studies the variation of ultrasonic biometric sensor TFT glass before thinning (500um) and after thinning (90um), as one single TFT glass contains more 500 TFT chip. The uniformity of TFT after thinning is very critical to the whole process. The variation in thickness of TFT glass will result in glass edge cracking or chipping during breaking or in on-going process. This, in turn, will affect the sensor function in some level. The uniformity in TFT glass thinning is a challenging process.
This paper applies Taguchi method, six sigma and DMAIC methodologies to define the scope and key characteristics of problems and evaluate data from different stages. Taguchi method is applied to design minimum DOE, evaluate factors and level to retrieve the best parameters of thinning process. Then effectiveness through process monitoring is confirmed. This paper applies “scientific-Taguchi” and “systematic-six Sigma, DMAIC” to analyze method and implement them in case study company to improve problem-solving in time reduction and cost saving.
Keywords: Taguchi method, Six Sigma, DMAIC, chemical etching and biometric (fingerprint) recognition

參考文獻
1.吳文傑、方明達、鄭錫勳、劉旭唐、何宗漢（2014）。以田口方法在不同的拋光參數下取得最佳玻璃移除率研究。工程科技與教育學刊，11(2)，252-263。
2.吳政霖（2014）。應用實驗設計法於透氣防水膜製程參數最佳化之研究。國立虎尾科技大學機械與機電工程研究所學位論文，雲林縣。
3.余豐榮、李義剛、鄭哲綸、邱稚淳（2013）。田口方法於鋁合金晶粒細化最佳壓縮參數之研究，Journal of Science and Engineering Technology，9(2)，77-85。
4.張展榮（2014）。以實驗設計法最佳化黃光製程對準之蝕刻參數。國立中興大學機械工程學系所學位論文，台中市。
5.黃乾怡、林宜鋒、紀勝財、蘇彥衍（2007）。田口方法應用於無鉛迴銲製程參數優化，Journal of Science and Engineering Technology，3(2)，99-111。
6.薛修忠（2010）。田口方法於切削中心加工機製程參數最佳化之應用—以石英玻璃表面加工為例。國立清華大學工業工程與工程管理學系工程碩士在職專班學位論文，新竹市。
7.衛彥榮（2016）。半導體電漿蝕刻機台減少汙染粒子型態缺陷與田口實驗分析。國立成功大學工程科學系碩士在職專班碩士論文，台南市。
取自https://hdl.handle.net/11296/86em6g。
8.鄭春生（2014）。品質管理：現代化觀念與實務應用。全華圖書。新北。
9.蘇朝墩（2013）。品質工程：線外方法與應用。前程文化。新北。
10.Al-Refaie, A., Li, M.-H. C., Chang, B.-C., & Jalham, I. (2012). Application of the Taguchi approach to improve performance of the alignment-layer printing process in liquid crystal displays. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 226(7), 1241–1248. https://doi.org/10.1177/0954405412442458
11.El-Axir, M. H., Elkhabeery, M. M., & Okasha, M. M. (2017). Modeling and Parameter Optimization for Surface Roughness and Residual Stress in Dry Turning Process. 7(5), 9.
12.Gun-Yong Hwang, Sang-Moon Hwang, Hong-Joo Lee, Ji-Hoon Kim, Keum-Shik Hong, & Lee, W.-Y. (2005). Application of Taguchi method to robust design of acoustic performance in IMT-2000 mobile phones. IEEE Transactions on Magnetics, 41(5), 1900–1903. https://doi.org/10.1109/TMAG.2005.846255
13.Kc, B., Faruk, O., Agnelli, J. A. M., Leao, A. L., Tjong, J., & Sain, M. (2016). Sisal-glass fiber hybrid biocomposite: Optimization of injection molding parameters using Taguchi method for reducing shrinkage. Composites Part A: Applied Science and Manufacturing, 83, 152–159. https://doi.org/10.1016/j.compositesa.2015.10.034
14.Lin, C.-S., Kao, T.-N., Chang, N.-C., Lin, N.-J., & Chen, S.-W. (2015). Quality improvement to the spinless coating process of touch panel with Taguchi methods. INDIAN J. ENG. MATER. SCI., 6.
15.Lin, C.-S., Shih, S.-J., Lu, A.-T., Hung, S.-S., & Chiu, C.-C. (2012). The quality improvement of PI coating process of TFT-LCD panels with Taguchi methods. Optik, 123(8), 703–710. https://doi.org/10.1016/j.ijleo.2011.06.028
16.Muttalib, M. F. A., Chen, R. Y., Pearce, S. J., & Charlton, M. D. B. (2017). Optimization of reactive-ion etching (RIE) parameters for fabrication of tantalum pentoxide (Ta 2 O 5 ) waveguide using Taguchi method. EPJ Web of Conferences, 162, 01003. https://doi.org/10.1051/epjconf/201716201003
17.Pundir, R., Chary, G. H. V. C., & Dastidar, M. G. (2018). Application of Taguchi method for optimizing the process parameters for the removal of copper and nickel by growing Aspergillus sp. Water Resources and Industry, 20, 83–92. https://doi.org/10.1016/j.wri.2016.05.001
18.Takatsuji, H., & Arai, T. (2000). Pinholes in Al thin "lms: Their e!ects on TFT characteristics and a taguchi method analysis of their origins. 8.

網路資源
1.IdentityONE，Fingerprint Technology Overview，http://www.identityone.net/BiometricTechnology.aspx
2.Mohammad Omar Derawi，Fingerprint，http://biometrics.derawi.com/?page_id=48
3.International Biometric Group(2003)，The Henry Classification System，https://web.archive.org/web/20110713000747/http:/static.ibgweb.com/Henry%20Fingerprint%20Classification.pdf
4.NYCHS(1997)，The Fingerprint System，http://www.correctionhistory.org/html/chronicl/dcjs/html/nyidbur2.html
5.李坚（2018.06.28） 手机生物识别的终极解决方案是什么https://www.ednchina.com/news/20180628-biometrics.html