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系統識別號 U0002-0107201017361100
中文論文名稱 利用單一觀測值建立監控製程變異之適應性多變量指數加權移動 平均管制圖
英文論文名稱 Multivariate Adaptive Exponentially Weighted Moving Average Control Charts for Monitoring Multivariate Process Variability with Individual Observations
校院名稱 淡江大學
系所名稱(中) 統計學系碩士班
系所名稱(英) Department of Statistics
學年度 98
學期 2
出版年 99
研究生中文姓名 陳怡婷
研究生英文姓名 Yi-Ting Chen
學號 697650041
學位類別 碩士
語文別 英文
口試日期 2010-06-04
論文頁數 48頁
口試委員 指導教授-蔡宗儒
委員-劉玉龍
委員-廖敏治
中文關鍵字 共變異矩陣  指數加權移動平均  單一觀測值  平均連串長度 
英文關鍵字 Covariance Matrix  Exponentially Weighted Moving Average  Individual Observation  Average Run Length 
學科別分類 學科別自然科學統計
中文摘要 本論文對單一觀測值建立監控製程變異之適應性多變量指數加權移動平均管制圖。
此一管制圖有助於針對製程變異提早發出警訊。並在模擬研究下, 我們利用數值分析法
找出不同條件下之最佳管制圖參數。相較於目前文獻中的方法, 數值分析的結果顯示,
本論文建議的管制圖可以有較佳的錯誤預警效果。
英文摘要 Based on an adaptive adjustment, this thesis provides a multivariate expo-
nentially weighted moving average control chart with individual observations.
This chart is used for monitoring shifts on process variances or correlation.
A computation procedure is give to determine the chart parameters. More-
over, some of these parameters are tabulated. Numerical results show that the
proposed variances or correlation with shorter average run lengths to alarm
out-of-control signals.
論文目次 Contents
1 Introduction 1
2 Literature Review 6
3 The Adaptive MEWMA Control Chart 10
4 Numerical Study 16
5 Conclusions 42
List of Tables
4.1 The values of L for different combinations of r and v when p=2 and
ARL0=200. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 The values of L for different combinations of r and v when p=2 and
ARL0=370. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.3 The values of L for different combinations of r and v when p=2 and
ARL0=500. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.4 The values of L for different combinations of r and v when p=3 and
ARL0=200. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.5 The values of L for different combinations of r and v when p=3 and
ARL0=370. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.6 The values of L for different combinations of r and v when p=3 and
ARL0=500. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.7 The values of L for different combinations of r and v when p=5 and
ARL0=370. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.8 The values of L for different combinations of r and v when p=5 and
ARL0=500. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.9 The values of L for different combinations of r and v when p=10 and
ARL0=370. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.10 The values of L for different combinations of r and v when p=10 and
ARL0=500. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.11 Out-of-control ARLs of AMEWMA for p = 2 and ARL0=370. . . . . . . . 29
4.12 Out-of-control ARLs of AMEWMA for p = 2 and ARL0=370. . . . . . . . 30
4.13 Out-of-control ARLs of AMEWMA for p = 2 and ARL0=370. . . . . . . . 31
4.14 Out-of-control ARLs of AMEWMA for p = 2 and ARL0=370. . . . . . . . 32
4.15 Out-of-control ARLs of AMEWMA for p = 2 and ARL0=370. . . . . . . . 33
4.16 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 34
4.17 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 35
4.18 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 36
4.19 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 37
4.20 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 38
4.21 Out-of-control ARLs of AMEWMA for p = 3 and ARL0=370. . . . . . . . 39
4.22 Performance comparison for various multivariate control charts with p = 2. 40
4.23 Performance comparison for various multivariate control charts with p = 2
and only q shifts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41


參考文獻 [1] Yeh, A. B., Huwang, L. and Wu C.-W. (2005). A multivariate EWMA control chart
for monitoring process variability with individual observations. IIE Transactions, 37:
1023-1035.
[2] Lowry, C. A., Woodall, W. H., Champ, C. W. and Rigdon, S. E. (1992). A multi-
variate exponentially weighted moving average control chart.Technometrics, 34(1):
46-53.
[3] Hawkins, D. M. (1981). A cuaum for a scale parameter, Journal of Quality Technology
, 13: 228-231.
[4] Hawkins, D. M. (1991). Multivariate quality control based on regression-adjusted
variables, Technometrics, 33(1): 61-75.
[5] Hawkins, D. M. (1993). Regression adjustment for variables in multivariate quality
control, Journal of Quality Technology, 25: 170-182.
[6] Huber, P. J. (1981). Robust Statistics. John Wiley and Sons. New York.
[7] Shu, L. (2008). An adaptive exponentially weighted moving average control chart
for monitoring process variances. Journal of Statistical Computation and Simulation,
78(4): 367-384
[8] Huwang, L, Yeh, A. B. and Wu C.-W. (2007). Monitoring multivariate process vari-
ability for individual observations. Journal of Quality Technology, 39(3): 258-278.
[9] Reynolds, M. R. Jr. and Stoumbos, Z. G. (2005). Should exponentially weighted mov-
ing average and cumulative sum charts be used with shewhart limits? Technometrics,
47(4): 409-424.
[10] Reynolds, M. R. Jr. and Kim, K. (2007). Multivariate control charts for monitoring
the process mean and variability using sequential sampling. Sequential Analysis, 26:
283-315.
[11] Montgomery, D. C., (2005). Statistical Quality Control, A Modern Introduction (6th
ed., Wiley, New York.).
[12] Yashchin, E., (1995). Estimating the current mean of a process subject to abrupt
changes. Technometrics, 37: 311-323.
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