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題名 數據相關之二階製程管制
Two-step Process Control for Autocorrelated data
作者 陳維倫
Chen, Wei-Lun
貢獻者 楊素芬
陳維倫
Chen, Wei-Lun
關鍵詞 autocorrelated
time series model
transfer model
cause-selecting control chart
日期 2001
上傳時間 15-Apr-2016 16:10:16 (UTC+8)
摘要 Most products are produced by several process steps and have more than one interested quality characteristics. If each step of the process is independent, and the observations taken from the process are also independent then we may use Shewhart control chart at each step. However, in many processes, most production steps are dependent and the observations taken from the process are correlated. In this research, we consider the process has two dependent steps and the observations taken from the process are correlated over time. We construct the individual residual control chart to monitor the previous process and the cause-selecting control chart to monitor the current process. Then simulate all the states occur in the process and present the individual residual control chart and the cause-selecting control chart of the simulations. Furthermore compare the proposed control charts with the Hotelling T2 control chart. At last, we give an example to illustrate how to construct the proposed control
參考文獻 Alwan, L. C and Roberts, H. V. (1988),“Time-Series Modeling for Statistical Process Control ”. Journal of Business & Economic Statistics, Vol, 6, pp87-95.
Alwan, L. C. (1992)“Effects of Autocorrelation on Control Chart Performance” Communications in Statistics-Theory, Vol.21(4) ,pp1025-1049.
Box, G. E. P and Jenkins, G. M. (1976) “Time Series Analysis: Forecasting and Control ”(Revised edition), Holden Day, San Francisco.
Gnandesikan, R. (1977) “Methods for Statistical Analysis of Multivariate Observation”Wiley, New York.
Hu, J. S. and Roan, C. (1996), “Changes Patterns of Time Series-Based Control Charts”. Journal of Quality Technology, Vol.28, pp302-312.
Johnson, N. and Wichern, D,“Applied Multivariate Statistical Analysis” Prentice-Hall, Englewood Cliffs, N.J.
Montgomery, D. C. and Mastrangelo, G. M. (1991),“Some Statistical Process Control Methods for Autocorrelated Data”. Journal of Quality Technology, Vol.23, pp179-204.
Peter, J. B and Richard, A. D. (1996)“Introduction to Time Series and Forecasting”
Tsay, R. S. and Tiao, G. C. (1985) "Use of canonical analysis in time series modelidentification", Biometrika, Vol.72, pp299-315.
Vasilopoulos, A. V. and Stamboulis, A. P. (1978), “Modification of Control Chart Limits in the Presence of Data Correlation”, Journal of Quality Technology, Vol.10, pp20-30.
Wardell, D. G., Moskowitz, H., and Plante, R. D. (1992),“Control Charts in the Presence of Data Correlation”, Management Science Vol.38, pp1084-1105.
Wardell, D. G., Moskowitz, H., and Plante, R. D. (1994),“Run-Length Distributions of Special-Cause Control Charts for Correlated Process”. Technometrics, Vol.36, pp3-17.
Wardell, Wade, R. and Woodall, W. (1993), “ A Review and Analysis of Cause-Selecting Control Charts”. Journal of Quality Technology, Vol.25, pp 161-169.
Wei Jiang, Tsui K-L and Woodall, W. (2000), “A New SPC Monitoring Method: The ARMA Chart” Technometrics Vol.42,pp399-410.
吳柏林(Wu, 1995).“時間數列分析導論” 華泰書局出版
林茂文(Lin, 1992).“時間數列分析與預測”華泰書局出版
葉小蓁(Yeh, 1998).“時間序列分析與應用”
描述 碩士
國立政治大學
統計學系
88354013
資料來源 http://thesis.lib.nccu.edu.tw/record/#A2002001355
資料類型 thesis
dc.contributor.advisor 楊素芬zh_TW
dc.contributor.author (Authors) 陳維倫zh_TW
dc.contributor.author (Authors) Chen, Wei-Lunen_US
dc.creator (作者) 陳維倫zh_TW
dc.creator (作者) Chen, Wei-Lunen_US
dc.date (日期) 2001en_US
dc.date.accessioned 15-Apr-2016 16:10:16 (UTC+8)-
dc.date.available 15-Apr-2016 16:10:16 (UTC+8)-
dc.date.issued (上傳時間) 15-Apr-2016 16:10:16 (UTC+8)-
dc.identifier (Other Identifiers) A2002001355en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/85142-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 88354013zh_TW
dc.description.abstract (摘要) Most products are produced by several process steps and have more than one interested quality characteristics. If each step of the process is independent, and the observations taken from the process are also independent then we may use Shewhart control chart at each step. However, in many processes, most production steps are dependent and the observations taken from the process are correlated. In this research, we consider the process has two dependent steps and the observations taken from the process are correlated over time. We construct the individual residual control chart to monitor the previous process and the cause-selecting control chart to monitor the current process. Then simulate all the states occur in the process and present the individual residual control chart and the cause-selecting control chart of the simulations. Furthermore compare the proposed control charts with the Hotelling T2 control chart. At last, we give an example to illustrate how to construct the proposed controlen_US
dc.description.tableofcontents 封面頁
證明書
致謝詞
論文摘要
目錄
表目錄
圖目錄
1. INTRODUCTION
2. THE PROCESS MODEL
2.1 Assumptions and Notation
2.2 The Possible Distribution of Xt and Yt
2.3 Process Control for the Previous and Current process
2.3.1 Establish the Individual Residual Chart to Monitor the Previous Process
2.3.2 Establish the Cause-Selecting Control Chart to Monitor the Current Process
2.4 Type I, Type II Error Probabilities and the Power of the Propose Control Chart
3. Simulation Study and An Empirical Example
3.1 Simulate 9 Process States
3.1.1 Simulate state 1 in the process
3.1.2 Simulate state 2 in the process
3.1.3 Simulate state 3 in the process
3.1.4 Simulate state 4 in the process
3.1.5 Simulate state 5 in the process
3.1.6 Simulate state 6 in the process
3.1.7 Simulate state 7 in the process
3.1.8 Simulate state 8 in the process
3.1.9 Simulate state 9 in the process
3.2 An Empirical Example
3.3 Comparison the proposed control chart and Hotelling T2 control chart
4. CONCLUSION
5. REFERENCES
6. APPENDICES
Appendix 1 (the empirical data to build the proposed charts)
Appendix 2 (the empirical data to build the proposed charts)
Appendix 3 (the S-plus program to count ARL for the simulated 9 states data)		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#A2002001355en_US
dc.subject (關鍵詞) autocorrelateden_US
dc.subject (關鍵詞) time series modelen_US
dc.subject (關鍵詞) transfer modelen_US
dc.subject (關鍵詞) cause-selecting control charten_US
dc.title (題名) 數據相關之二階製程管制zh_TW
dc.title (題名) Two-step Process Control for Autocorrelated dataen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Alwan, L. C and Roberts, H. V. (1988),“Time-Series Modeling for Statistical Process Control ”. Journal of Business & Economic Statistics, Vol, 6, pp87-95.
Alwan, L. C. (1992)“Effects of Autocorrelation on Control Chart Performance” Communications in Statistics-Theory, Vol.21(4) ,pp1025-1049.
Box, G. E. P and Jenkins, G. M. (1976) “Time Series Analysis: Forecasting and Control ”(Revised edition), Holden Day, San Francisco.
Gnandesikan, R. (1977) “Methods for Statistical Analysis of Multivariate Observation”Wiley, New York.
Hu, J. S. and Roan, C. (1996), “Changes Patterns of Time Series-Based Control Charts”. Journal of Quality Technology, Vol.28, pp302-312.
Johnson, N. and Wichern, D,“Applied Multivariate Statistical Analysis” Prentice-Hall, Englewood Cliffs, N.J.
Montgomery, D. C. and Mastrangelo, G. M. (1991),“Some Statistical Process Control Methods for Autocorrelated Data”. Journal of Quality Technology, Vol.23, pp179-204.
Peter, J. B and Richard, A. D. (1996)“Introduction to Time Series and Forecasting”
Tsay, R. S. and Tiao, G. C. (1985) "Use of canonical analysis in time series modelidentification", Biometrika, Vol.72, pp299-315.
Vasilopoulos, A. V. and Stamboulis, A. P. (1978), “Modification of Control Chart Limits in the Presence of Data Correlation”, Journal of Quality Technology, Vol.10, pp20-30.
Wardell, D. G., Moskowitz, H., and Plante, R. D. (1992),“Control Charts in the Presence of Data Correlation”, Management Science Vol.38, pp1084-1105.
Wardell, D. G., Moskowitz, H., and Plante, R. D. (1994),“Run-Length Distributions of Special-Cause Control Charts for Correlated Process”. Technometrics, Vol.36, pp3-17.
Wardell, Wade, R. and Woodall, W. (1993), “ A Review and Analysis of Cause-Selecting Control Charts”. Journal of Quality Technology, Vol.25, pp 161-169.
Wei Jiang, Tsui K-L and Woodall, W. (2000), “A New SPC Monitoring Method: The ARMA Chart” Technometrics Vol.42,pp399-410.
吳柏林(Wu, 1995).“時間數列分析導論” 華泰書局出版
林茂文(Lin, 1992).“時間數列分析與預測”華泰書局出版
葉小蓁(Yeh, 1998).“時間序列分析與應用”		zh_TW