簡易檢索 / 詳目顯示

研究生: 黃翊恆
論文名稱: 利用Proportional Odds 模式來監控輪廓製程
Monitoring Profiles based on Proportional Odds Models
指導教授: 黃榮臣
口試委員: 楊素芬
王藝華
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: 2012
畢業學年度: 100
語文別: 中文
論文頁數: 69
中文關鍵詞: 輪廓監控EWMA管制圖
相關次數: 點閱:2下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 在許多實際的例子上,產品或製程的品質特徵可以用一個反應變數和一個或多個解釋變數來描述,這種函數關係稱為輪廓曲線。本文主要是針對有序的類別型資料反應變數與解釋變數之間的輪廓關係來進行製程監控,而我們是用proportional odds 模式來描述這兩者之間的輪廓關係。在這個模式之下我們建構兩個管制圖來進行輪廓模型的監控,並在偵測出失控訊號之後,進行製程改變點的估計以及參數改變的診斷。最後我們舉一個例子來說明實際上如何操作使用我們所提出的管制圖。


    摘要 2 第1章 緒論 1 1.1 前言 1 1.2 輪廓監控 3 1.3 研究動機與目的 5 第2章 Proportional odds 模式 7 2.1 Proportional odds 模式 7 2.2 參數估計 8 2.3 監控參數管制圖 12 2.4 診斷 14 第3章 平均連串長度的比較 16 3.1 比較準則以及管制上限的求法 16 3.2 管制圖效率的比較 18 3.3 診斷的比較 22 3.4 例子 25 第4章 結論 29 參考文獻 32 附表 35

    [1] Agresti, A. (2007). An Introduction to Categorical Data Analysis, 2nd ed. John Wiley & Sons, Inc. New York, NY.

    [2] Colosimo, B. M., and Pacella, M. (2007). “On the Use of Principal Component Analysis to Identify Systematic Patterns in Roundness Profiles”. Quality and Reliability Engineering International 23, pp. 707-725.

    [3] Ding, Y., Zeng, L., and Zhou, S. (2006). “Phase I Analysis for Monitoring Nonlinear Profiles in Manufacturing Processes”. Journal of Quality Technology 38, pp. 199-216.

    [4] Jin, J., and Shi, J. (1999). “Feature-Preserving Data Compression of Stamping Tonnage Information Using Wavelet”. Technometrics 41, pp. 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, pp. 418-426.

    [6] Kim, K., Mahmoud, M. A., and Woodall, W. H. (2003). “On the Monitoring of Linear Profiles”. Journal of Quality Technology 35, pp. 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, pp. 79-90.

    [8] 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, 99. 247-268.

    [9] Mestek, O., Pavlik, J., and Suchanek, M. (1944). “Multivariate Control Charts: Control Charts for Calibration Curves”. Journal of Analytical Chemistry 350, pp. 344-351.

    [10] Montgomery, D. C. (2009). Introduction to Statistical Quality Control, 6th ed. John Wiley & Sons, Inc. New York, NY.

    [11] Page, E. S. (1954). “Continuous Inspection Schemes”. Biometrics 41, pp. 100-114.

    [12] Roberts, S. W. (1959). “Control Chart Tests Based on Geometric Moving Average”. Technometrics 1, pp. 239-250.

    [13] Stover, F. S., and Brill, R. V. (1998). “Statistical Quality Control Applied to Ionchromatography Calibrations”. Journal of Chromatography A 804, pp. 37-43.

    [14] Wald, A. (1939). “Contributions to the Theory of Statistical Estimation and Testing Hypotheses”. The Annals of Mathematical Statistics, 10, pp. 299-326.

    [15] Walker E., and Wright, S. (2002). ”Comparing Curves Using Additive Models”. Journal of Quality Technology 34, pp. 118-129.

    [16] 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, pp. 925-941.

    [17] 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, pp. 216-235.

    [18] Zou, C., Zhang, Y., and Wang, Z. (2006). “Control Chart Based on Change-point Model for Monitoring Linear Profiles”. IIE Transactions 38, pp. 1093-1103.

    [19] Zou, C., Tsung, F., and Wang, Z. (2007). “Monitoring General Linear Profiles Using Multivariate Exponentially Weighted Moving Average Schemes”. Technometrics 49, pp. 395-408.

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE