以懲罰樣條迴歸方法來對曲線品質特徵做第一階段的監控

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研究生：	許廷彰
論文名稱：	以懲罰樣條迴歸方法來對曲線品質特徵做第一階段的監控
指導教授：	黃榮臣
口試委員:
學位類別：	碩士 Master
系所名稱：	理學院 - 統計學研究所 Institute of Statistics
論文出版年：	2010
畢業學年度：	98
語文別：	中文
論文頁數：	71
中文關鍵詞：	無母數迴歸、懲罰項、懲罰樣條迴歸、混合模型、管制圖、輪廓監控
外文關鍵詞：	nonparametric regression, penalty, penalized spline regression, mixed model, control chart, profile monitoring
相關次數：	點閱：3 下載：0
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在許多實際情況中，產品或產品製程的品質特性經常是以一個反應變數對應一個或多個解釋變數的函數關係來描述，我們將這種反應變數與解釋變數之間的函數關係稱之為輪廓，並稱其資料型態為輪廓型資料。在監控製程時，經常遇到在管制圖的第一階段中無法事先知道輪廓的函數型態，針對此種情形，本文採用懲罰樣條迴歸模型來對輪廓資料做配適，並將其視為一線性混合模型來估計其模型中的迴歸參數，再以此迴歸參數估計量建構三種監控輪廓製程的管制圖。我們以常用的失控警訊機率當做準則，透過統計模擬的方式，比較這三種管製圖在不同類型參數偏移下的優劣，最後舉例說明如何實際操作和使用。

目錄
第一章    緒論........................................................1
1    前言........................................................1
2    輪廓監控....................................................3
3    研究動機與目的..............................................5
第二章    無母數迴歸模型之輪廓監控....................................7
1    無母數迴歸模型..............................................7
2    樣條函數與懲罰項............................................8
3    平滑參數、節點個數、節點位置與階數的選擇....................10
4    模型假設...................................................11
5    參數估計...................................................12
6    建構管制圖.................................................15
第三章    管制圖之建立與比較.........................................17
1    平衡的資料.................................................17
2    管制圖的比較準則...........................................17
3    模擬設定...................................................17
3.1    模型假設...........................................17
3.2    參數變動...........................................18
4    管制圖偵測能力之比較.......................................19
4.1    管制上限...........................................19
4.2    異質點.............................................20
4.3    階梯式偏移.........................................22
5    實例分析...................................................23
第四章    結論與未來研究.............................................26
附表...............................................................28

                                

參考文獻：
[1] Colosimo, B. M., and Pacella, M. (2007), “On the Use of Principle Component Analysis to Identify Systematic Patterns in Roundness Profiles,” Quality and Reliability Engineering International, 23, 707-725.
[2] Ding, Y., Zeng, L., and Zhou, S. (2006), “Phase I Analysis for Monitoring Nonlinear Profiles in Manufacturing Processes,” Journal of Quality Technology, 38, 199-216.
[3] Gupta, S., Montgomery, D. C., and Woodall, W. H. (2006), “Performance Evaluation of Two Methods for Online Monitoring of Linear Calibration Profiles,” International Journal of Production Research, 44, 1927-1942.
[4] Jin, J., and Shi, J. (1999), “Feature-Preserving Data Compression of Stamping Tonnage Information Using Wavelet,” Technometrics, 41, 327-339.
[5] Kang, L., and Albin, S. L. (2000), “On-Line Monitoring When the Process Yields a Linear Profile,” Journal of Quality Technology, 32, 418-426.
[6] Kim, K., Mahmoud, M. A., and Woodall, W. H. (2003), “On the Monitoring of Linear Profiles,” Journal of Quality Technology, 35, 317-328.
[7] Lada, E. K., Lu, J.-C., and Wilson, J. R. (2002), “A Wavelet-Based Procedure for Process Fault Detection,” IEEE Transactions on Semiconductor Manufacturing, 15, 79-90.
[8] Mahmoud, M. A., and Woodall, W. H. (2004), “Phase I Analysis of Linear Profiles with Calibration Applications,” Technometrics, 46, 380-391.
[9] Mahmoud, M. A., Parker, P. A., Woodall, W. H., and Hawkins, D. M. (2007), “A Change Point Method for Linear Profile Data,” Quality and Reliability Engineering International, 23, 247-268.
[10] Mestek, O., Pavlik, J., and Suchanek, M. (1994), “Multivariate Control Charts: Control Charts for Calibration Curves,” Journal of Analytical Chemistry, 350, 344-351.
[11] Montgomery, D. C. (2009), “Statistical Quality Control: A Modern Introduction,” John Wiley & Sons, New York.
[12] Rao, C. R. (1973), “Linear Statistical Inference and Its Application,” John Wiley & Sons, New York.
[13] Robinson, G. K. (1991), “That BLUP is a Good Thing: The Estimation of Random Effects,” Statistical Science, 6, 15-51.
[14] Rousseeuw, P. J. (1984), “Least Median of Squares Regression,” Journal of the American Statistical Association, 79(388), 871-880.
[15] Ruppert, D., Wand, M. P., and Carroll, R. J. (2003), “Semiparametric Regression,” Cambridge University Press.
[16] Searle, S. R., Casella, G., and McCulloch, C. E. (1992), “Variance Components,” John Wiley & Sons, New York.
[17] Stover, F. S., and Brill, R. V. (1998), “Statistical Quality Control Applied to Ion Chromatography Calibrations,” Journal of Chromatography A, 804, 37-43.
[18] Walker, E., and Wright, S. P. (2002), “Comparing Curves Using Additive Models,” Journal of Quality Technology, 34, 118-129.
[19] Williams, J. D., Birch, J. B., Woodall. W. H., and Ferry, N. M. (2007), “Statistical Monitoring of Heteroscedastic Dose-Response Profiles from High-Throughput Screening,” Journal of Agricultural, Biological, and Environmental Statistics, 12, 216-235.
[20] Williams, J. D., Woodall, W. H., and Birch, J. B. (2007), “Statistical Monitoring of Nonlinear Product and Process Quality Profiles,” Quality and Reliability Engineering International, 23, 925-941.
[21] Woodall, W. H. (2007), “Current Research on Profile Monitoring,” Revista Produção, 17, 420-425.
[22] Woodall, W. H., Spitzner, D. J., Montgomery, D. C., and Gupta, S. (2004), “Using Control Charts to Monitor Process and Product Quality Profiles,” Journal of Quality Technology, 36, 309-320.
[23] Zou, C., Tsung, F., and Wang, Z. (2007), “Monitoring General Linear Profiles Using Multivariate EWMA Schemes,” Technometrics, 49, 395-408.
[24] Zou, C., Zhang, Y., and Wang, Z. (2006), “Control Chart Based on Change-Point Model for Monitoring Linear Profiles,” IIE Transactions, 38, 1093-1103.
[25] 翁崢珮 (2004), “Profile Monitoring by Nonparametric Regression,” 國立交通大學碩士論文.

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