在業界實際應用製程能力分析工具過程中，可以發現透過傳統計算得到之製程能力指標與現場產品製程能力水準有不吻合的現象產生。其主要的原因在於：大多數企業在進行抽樣檢驗產品品質時，往往受到時間、成本與人力配置上的考量，無法以全檢或大量抽樣的方式來取得母體分配的平均數與標準差。是故，往往都是藉由少量的樣本資料來推估製程各參數值，才能得到產品製程能力的估計值；但是，一般企業最常用的製程能力指標值（如： 、 、 、 等），基本上皆定義在：假設所蒐集的製程資料是服從常態分配，或屬於常態性製程。而Chou et al.（1990）指出：以傳統製程能力指標的估計值來判定小樣本下之製程是否合乎產品規格，是不夠嚴謹與不恰當的方法。因易受到抽樣數量過少而產生其變異數過大的影響，終究產生抽樣誤差使得無法反應出產品真正的製程能力指標與良率值。因此，本研究提出利用Box-Cox轉換式的代換使得小樣本所得數值能夠透過此公式將彼此間的變異數縮小，能夠逼近服從常態分配。再計算一般小樣本下t分配之相關的製程能力指標與製程良率公式，且進行整體製程良率之分析與探討。

　　而本研究所得結論為以下諸點：從Box-Cox公式之轉換前後的變異縮減程度來看，整體針對望目型、望大型、及望小型製程規格之減少原模擬數值的變異程度可達百分之四十九（49%）；在本研究所提方式與傳統小樣本抽檢方式之差異點：望目型產品規格中若使用傳統小樣本抽檢方式進行計算 與 時，有顯著性低估現象；反正在計算 、 、 、及 則會有顯著性高估現象；以實務針對TFT-LCD內各項關鍵品質特性與整體製程能力概況進行個案分析的應用。

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Balamurali,S.,(2003),“Bootstrap Condifence Limits for Short-Run Capability Indices”,Quality Engineering,15(4).pp.643-648.

Box, G. E. P. and D. R. Cox, “An analysis of transformation”, Journal of the Royal Statistical Society, Series B, 26,pp.211-246.

Boyles,R.A.,(1991),“The Taguchi Capability Index”, Journal of Quality Technology, 23(1),pp.17-26.

Boyles,R.A.,(1994),“Process Capability with asymmetric Tolerance”, Communications in Statistics: Computation & Simulation, 23(3), pp.615-643.

Chan,L.K., Cheng,S.W.& Spiring,F.A.,(1988),“A new measure of process capability: Cpm.”, Journal of Quality Technology,20(3),pp.162-175.

Chen, H.,(1994), “A Multivariate Process Capability Index over a Rectangular Solid Tolerance Zone”, Statistic Sinica, 4,pp.749-758.

Chen,K.S.,Huang,M.L.and Li,R.K.,(2001),“Process Capability Analysis for an Entire Production”, International Journal of Production Research,39(17),pp.4077-4087.

Chou, Y. M., Owen, D. B & Borrego A, S. A., (1990), “Lower Confidence Limits on Process Capability Indices”, Communication in statistic---Theory and Method,18(12), pp.4549-4560.

Clements,J.A.,(1989),“Process Capability Calculations for Non-normal Distributions”, Quality Process,September,pp.95-100.

Davis, R. D., Kaminsky, F. C. and Saboo, S., (1992), “Process Capability Analysis for Processes With Either a Circular or a Spherical Tolerance Zone”, Quality Engineering, 5(1),pp.41-54.

English, J. R., and Taylor, G. D., (1993), “Process Capability Analysis A Robustness Study”, International Journal of Production and Research , 31(7),pp.1621-1635.

Huang, M. L., Chen, K. S., Hung, Y. H.,(2002), “Integrated Process Capability Analysis with an Application in Backlight Module”, Microelectronics Reliability, 42,pp.2009-2014.

Juran, J.M.(1974),Jurans Quality Control Handbook.3rd Edition, McGraw Hill, New York.

Kane,V.E.,(1986),“Process capability indices”,Journal of Quality Technology,18(1),pp.41-52.

Montgomery, D. C.,(2001), Introduction to Statistical Quality Control. Wiley, New York.

Pearn,W.L., Kotz,S. & Johnson,N.L.,(1992),“Distributional and Inferential Properties of Process Capability Indices”, Journal of Quality Technology,24(4),pp.216-231.

Pearn,W.L. and Chen,K.S.,(1995),“Estimating Process Capability Indices for Non-normal Pearsonian Populations”, Quality & Reliability Engineering International,11(5),pp.386-388.

Pearn,W.L., Lin,G.h. & Chen,K.S.,(1998),“Distributional and Inferential Properties of the Process Accuracy and Process Precision Indices”,Commun Stat-Theory Meth,27(4),pp.985-1000.

Shahriari, H. Hubele, N. F. and Lawrence, F.P.,(1995), “A Multivariate Process Capability Vector”, Proceedings of the 4th Industrial Engineering Research Conference, Nashville, TN,pp.303-308.

Singhal,S.C.,(1991), Multiprocess Performance Analysis Chart(MPPAC) with Capability Zones. Quality Engineering,4(1),pp.75-81.

Taam, W. Subbaiah, P. and Liddy, J. W., (1993), “A Note on Multivariate Capability Indices”, Journal of Applied Statistics , 20, pp.339-351.

Yeh, A. B. and Chen, H., (2001), “A Nonparametric Multivariate Process Capability Index”, International Journal of Modeling and Simulation, 21(3) ,pp.218-223.