偵測變異的多變量管制圖之研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：10

、訪客IP：3.144.172.115

姓名

謝昀霖(Chaos Xie) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

偵測變異的多變量管制圖之研究

相關論文

★ 診斷多變量管製圖之研究	★ 複合設計的研究
★ 超飽和設計的研究	★ 股價預測之統計模型
★ 實驗的特殊設計及動態數據的分析	★ 半反摺追蹤設計之探討
★ 三水準因子實驗離散效應的研究	★ PB設計的投影性質研究
★ 分徑指標在建立決策樹的比較	★ 不同製程模式下比例積分回饋控制器之研究
★ 特定交互之部分因子設計	★ 偵測設限資料之EWMA管制方法
★ 實驗徑大小為32之最小偏誤集區分割設計	★ 集區大小為二的兩水準因子集區設計
★ 選取多變量特性值最理想條件的方法之比較	★ 利用六標準差管理提昇中小企業之產品品質—以塑膠產業霧度改善為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

由於製程日趨複雜，需要管制的品質特性也越來越多，而且通常品質特性之間都會有相關性，所以利用單變量管制圖做個別的監控容易產生誤判的機會，故多變量管制圖應運而生。
利用多變量管制圖作管制，會有一個運用上的問題，也就是當多變量管制圖出現警訊時，無法確定是那一個或那一些品質特性出現了問題。這個問題在偵測目標的多變量管制圖已經有一有效的方法，Mason,Tracy and Young（1995）提出利用出現警訊時的Hotelling’s T2做分解，去檢視是那些品質特性出了問題。
但是在偵測變異的多變量管制圖尚無一明確的方法來解決此問題。故我們利用Tang and Barnett（1996a）中變異數矩陣分解和Mason,Tracy and Young（1995）的作法之概念，將樣本變異數矩陣的行列式值作分解，再利用分解後的統計量來判斷是那一個或那一些品質特性出現了問題。

關鍵字(中)

★ 多變量
★ 管制圖
★ 變異源

關鍵字(英)

★ Control Chart
★ out of control
★ Multivariate

論文目次

摘要...................................................................... I
目錄..................................................................... II
圖目錄.................................................................. III
表目錄................................................................... IV
第一章緒論............................................................... 1
第二章多變量管制圖....................................................... 7
2. 1 W 管制圖............................................................ 13
2. 2 S 管制圖............................................................ 14
2. 3 S 管制圖............................................................ 15
2. 4 實例................................................................ 17
2. 5 其他相關的研究...................................................... 23
第三章研究變異數多變量管制圖的變異源.................................... 33
3. 1 變異數的多變量統計量之分解.......................................... 33
3. 2 分解後統計量的判斷準則.............................................. 35
3. 3 實例................................................................ 40
3. 4 建議探討變異源的步驟................................................ 43
3. 5 確認分解後統計量分佈................................................ 46
第四章結論與未來展望.................................................... 55
4. 1 結論................................................................ 55
4. 2 未來展望............................................................ 56
參考文獻.............................................................. 58

參考文獻

李俊霖（1997）「二元Shewhart管制法則之研究與應用─針對多變量特性之製程」，碩士論文，國立台灣大學工業工程學研究所。
葉珮甄（1998）「多變量統計製程管制應用在具有多種變異來源的製程上─以半導體製程為例」，碩士論文，國立臺灣大學工業工程學研究所。
王亞倫（1999）「診斷多變量管製圖之研究」，碩士論文，國立中央大學工業管理研究所。
顏家鈴（2001）「監控多變量製程變異性增加之管制圖」，碩士論文，國立交通大學統計所。
吳建瑋（2001）「監控單一觀測值之多變量製程變異性管制圖」，碩士論文，國立清華大學統計學研究所。
吳政儀（2001）「在單一觀測值下監控多變量製程變異性之EWMA管制圖」，碩士論文，國立清華大學統計學研究所。
游明新（2002）「多變量管制圖之比較與探討」，碩士論文，雲林科技大學工業工程與管理研究所。
黃立芬（2002）「監控多變量製程變異性增加之EWMA管制圖」，碩士論文，國立交通大學統計所。
蘇俊虢（2003）「非常態性對T2管制圖的效應評估」，碩士論文，中原大學工業工程研究所。
Alt, F.B. (1985). Multivariate Quality Control, The Encyclopedia of Statistical Sciences, Kotz S., Johnson, N. L. and Read, C. R. (eds), John Wiley & Sons, New York.
Alt, F. B. and Smith, N. D. (1988). Multivariate Process Control, Handbook of Statistics, P. R. Krishnaiah and C. R. Rao (eds), North-Holland: Elsevier Science Publishers B.V., 7.
Anderson, T. W. (1984). An Introduction to Multivariate Statistical Analysis,
2th edition, John Wiley & Sons, New York.
Aparisi, F.; Jabaloyes, J. and Carrion, A. (1999). “Statistical Properties of
the S Multivariate Control Chart”. Communications in Statistics -
Theory and Methods, 28(11), pp.2671-2686.
Aparisi, F.; Jabaloyes, J. and Carrion, A. (2001). “Generalized Variance
Chart Design with Adaptive Sample Sizes. The Bivariate Case”.
Communications in Statistics - Simulation and Computation, 30(4), pp.
931-948.
Champ, C. W. and Chou, S. P. (2003). “Comparisons of Standard and
Individuals Limits Phase I Shewhart X , R and S Charts”. Quality
and Reliability Engineering International, 19(2), pp. 161-170.
Chang, T. C. and Gan, F. F. (1995). “A Cumulative Sum Control Chart for
Monitoring Process Variance”. Journal of Quality Technology, 27(2),
pp. 109-119.
Crosier, R. B. (1988). “Multivariate Generalizations of Cumulative Sum
Quality-Control Schemes”. Technometrics, 30(3), pp. 291-303.
Crowder, S. V. and Hamilton, M. (1992). “An EWMA for Monitoring a
Standard Deviation”. Journal of Quality Technology, 24(1), pp. 12-21.
Djauhari, M. A. (2005). “Improved Monitoring of Multivariate Process
Variability”. Journal of Quality Technology, 37(1), pp. 32-39.
Domangue, R. and Patch, S. C. (1991). “Some Omnibus Exponentially
Weighted Moving Average Statistical Process Monitoring Schemes”.
Technometrics, 33(3), pp. 299-313.
Grigoryan, A. and He, D. (2005). “Multivariate double sampling S charts for
controlling process variability”. International Journal of Production
Research, 43(4), pp. 715-730.
Hawkins, D. M. and Olwell, D. H. (1998). Cumulative Sum Charts and
Charting for Quality Improvement, Springer Verlag, New York.
Healy, J. D. (1987). “A Note on Multivariate CUSUM Procedures”.
Technometrics, 29(4), pp. 409-412.
Khoo, B. C. and Quah, S. H. (2003). “Multivariate Control Chart for Process
Dispersion Based on Individual Observations”. Quality Engineering,
15(4), pp. 639-642.
Klein, M. (2000). “Modified S-Charts for Controlling Process Variability”.
Communications in Statistics - Simulation and Computation, 29(3), pp.
919-940.
Lowry, C. A. ; Champ, C. W., and Woodall, W. H. (1995). “The
Performance of Control Charts for Monitoring Process Variation”.
Communications in Statistics – Simulation and Computation, 24(1-2),
pp. 409-437.
Lowry, C. A.; Woodall, W. H.; Champ, C. W. and Rigdon, S. E. (1992). “A
Multivariate EWMA Control Chart”. Technometrics, 34(1), pp. 46-53.
Lucas, J. M. and Saccucci, M. S. (1990). “Exponentially Weighted Moving
Average Control Schemes: Properties and Enhancements”.
Technometrics, 32(1), pp. 1-12.
MacGregor, J. F. and Harris, T. J. (1993). “The Exponentially Weighted
Moving Variance”. Journal of Quality Technology, 25(2), pp. 106-118.
Mason, R. L.; Chou, Y. M.; Sullivan, J. H.; Stoumbos, Z. G. and Young, J. C.
(2003). “Systematic Patterns in T2 Charts”. Journal of Quality
Technology, 35(1), pp.47-58.
Mason, R. L.; Chou, Y. M. and Young, J. C. (2001). “Applying Hotelling’s
T2 statistic to Batch Processes”. Journal of Quality Technology, 33(4),
pp. 466-479.
Mason, R. L.; Tracy, N. D. and Young, J. C. (1995). “Decomposition for
Multivariate Control Chart Interpretation”. Journal of Quality
Technology, 27(2), pp. 99-108.
Mason, R. L.; Tracy, N. D. and Young, J. C. (1997). “A Practical Approach
for Interpreting Multivariate T2 Control Chart Signals”. Journal of
Quality Technology, 29(4), pp. 396-406.
Mason, R. L.; Tracy, N. D. and Young, J. C. (1999). “Improving the
Sensitivity of the T2 Statistic in Multivariate Process Control”. Journal
of Quality Technology, 31(2), pp. 155-165.
McKay, R. J. (1989). “Simultaneous procedures for covariance matrices”.
Communications in Statistics - Theory and Methods, 18(2), pp.
429-443.
Montgomery, D. C. (2001). Introduction to Statistical Quality Control, 4th
Edition. John Wiley & Sons, New York.
Pignatiello, J. J. and Runger, G. C. (1990). “Comparisons of Multivariate
CUSUM Charts”. Journal of Quality Technology, 22(3), pp. 173-186.
Prabhu, S. S. and Runger, G. C. (1997). “Designing a Multivariate EWMA
Control Chart”. Journal of Quality Technology, 29(1), pp. 8-15.
Reynolds, M. R.; Amin, R. W.; Arnold, J. C. and Nachlas, J. A. (1988). “ X
Charts with Variable Sampling Intervals”. Technometrics, 30(2), pp.
181-192.
Roes, K. C. B., Does, R. J. M. M. and Schuring, Y. (1993). “Shewhart-type
Control Charts for Individual Observations”. Journal of Quality
Technology, 25(3), pp. 188-198.
Runger, G. C.; Keats, J. B.; Montgomery, D. C. and Scranton, R. D. (1999).
“Improving the Performance of the Multivariate EWMA Control
Chart”. Quality and Reliability Engineering International, 15(3), pp.
161-166.
Sim, C. H. (2000). “S-Chart for Non-Gaussian Variables”. Journal of
Statistical Computation and Simulation, 65(2), pp. 147-156.
Srivastava, M. S. (1997). “CUSUM procedure for Monitoring Variability”.
Communications in Statistics - Theory and Methods, 26(12), pp.
2905-2926.
Steiner, S. H. (1999). “EWMA Control Charts with Time-Varying Control
Limits and Fast Initial Response”. Journal of Quality Technology, 31(1),
pp. 75-86.
Sullivan, J. H. and Woodall, W.H. (1996a). “A Control Chart for
Preliminary Analysis of Individual Operations”. Journal of Quality
Technology, 28(3), pp. 265-278.
Sullivan, J. H. and Woodall, W. H. (1996b). “A Comparison of Multivariate
Control Charts for Individual Observations”. Journal of Quality
Technology, 28 (4), pp. 398-408.
Tang, P. F. and Barnett, N. S. (1996a). “Dispersion Control for Multivariate
Processes”. The Australian Journal of Statistics, 38(3), pp. 235-251.
Tang, P. F. and Barnett, N. S. (1996b). “Dispersion Control for Multivariate
Processes- some comparisons”. The Australian Journal of Statistics,
38(3), pp. 253-273.
Tracy, N. D.; Young, J. C. and Mason, R. L. (1992). “Multivariate Control
Charts for Individual Observations”. Journal of Quality Technology,
24(2), pp. 88-95.
Tsung, F. and Apley, D. W. (2002). “The dynamic T2 Chart for monitoring
feedback - controlled processes”. IIE Transactions, 34(12), pp.
1043-1053.
Vargas, J. A. (2003). “Robust Estimation in Multivariate Control Charts for
Individual Observations”. Journal of Quality Technology, 35(4), pp.
367-376.
Woodall, W. H. (1997). “Control Charts Based on Attribute Data:
Bibliography and Review”. Journal of Quality Technology, 29(2), pp.
172-183.
Woodall, W. H. and Ncube, M. M. (1985). “Multivariate CUSUM Quality
Control Procedures”. Technometrics, 27(3), pp. 285-292.

指導教授

王丕承(PC Wang)

審核日期

2005-7-7

推文