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題名 追蹤季節性時間數列模型之流程資料
Monitoring process data with seasonal time series model作者 王儀茹 貢獻者 楊素芬<br>鄭宗記
王儀茹關鍵詞 季節性時間數列
信賴帶
自我相關製程
Seasonal time series model
Confidence band
Autocorrelated process日期 2012 上傳時間 2-九月-2013 15:36:09 (UTC+8) 摘要 追蹤季節性時間數列模型之流程資料
Control charts are designed and evaluated under the assumption that the observations from the process are independent and identically distributed. However, the independence assumption is often violated in practice. Autocorrelation may be represented in many processes. To solve this problem, it is becoming more common to obtain profiles at each time period. Profile monitoring is the use of control charts for cases in which the quality of a process or product can be characterized by a functional relationship between a response variable and one or more explanatory variables. For the data with seasonal time series model, we propose several monitoring approaches to detect the out-of-control profiles. After considering both Phase I and Phase II schemes, a real example is given to illustrate the results.參考文獻 Alwan, L. C. and Roberts, H. V. (1988). Time-Series Modeling for Statistical Process Control. Journal of Business & Economic Statistics, 6(1):87-95.Box, G.E.P., Jenkins, G.M.,Reinsel G.C. (2008). Time series Analysis: Forecasting and Control, 4th ed. New York: John Wiley and Sons.Brockwell, P. J. and Davis, R. A. (2009). Time Series: Theory and Methods, 2nd ed. New York: Springer-Verlag.Cheng, T-C and Yang, S-F. (2013). Monitoring Profile Based on a Linear Regression Model with Correlated Errors.Ding, Y., Zeng, L., Zhou, S. (2006). Phase I Analysis for Monitoring Nonlinear Profiles in Manufacturing Processes. Journal of Quality Technology, 38(3), 199–216.Durbin,J.,Koopman, S.J. (2001). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.Eyvazian, M., Noorossana, R., Saghaei, A. & Amiri, A. (2011). Phase II Monitoring of Multivariate Multiple Linear Regression Profiles. Quality and Reliability Engineering International, 27, 281-296.Gupta,S.,Montgomery D.C.,Woodall W.H. (2006). Performance evaluation of two methods for online monitoring of linear calibration profiles. International Journal of Production Research, 44, 1927-1942.Harvey, A. (1989). Forecasting, Structural Time Sereis Models and the Kalman Filter. Cambridge: Cambridge University Press.Jensen, W.A., Birch, J.B., Woodall, W.H. (2008). Monitoring correlation within linear profiles using mixed models. Journal of Quality Technology, 40, 167-183.Jensen,W.A.,Birch, J.B. (2009). Profile monitoring via nonlinear mixed models. Journal of Quality Technology, 41, 18-34.Kang, L., Albin, S.L. (2000). On-Line Monitoring When the Process Yields a Linear Profile. Journal of Quality Technology, 32, 418–426.Kang, L., Albin, S.L. (2000). On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32, 418-426.Kazemzadeh, R.B., Noorossana, R., Amiri, A. (2008). Phase I Monitoring of Polynomial Profiles. Communications in Statistics-Theory and Methods, 37, 1671-1686.Kim, K., Mahmoud, M.A., Woodall, W.H. (2003). On the Monitoring of Linear Profiles. Journal of Quality Technology, 35, 317–328.Kim, K., Mahmoud, M.A., Woodall, W.H. (2003). On the Monitoring of Linear Profiles. Journal of Quality Technology, 35, 317-328.Lowry, C. A. and Montgomery, D. C. (1995). A Review of Multivariate Control. IIE Transactions, 27, 800-810.Lu, C. W. and Reynolds, M. R., Jr. (1999a). Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes. Journal of Quality Technology, 31, 259-274.Montgomery, D. C. (2005). Introduction to statistical quality control, 5nd edn. John Wiley, New York.Noorossana, R., Eyvazian, M., Amiri, A., Mahmoud, M.A. (n.d.). "Statistical Monitoring of Multivariate Multiple Linear Regression Profiles in Phase I with Calibration Application. Quality and Reliability Engineering International, 26, 291-303.Noorossana, R., Amiri, A., Soleimani, P. (2008). On the Monitoring of Autocorrelated Linear Profiles. Communications in Statistics-Theory and Methods, 37, 425-442.Noorossana, R., Eyvazian, M., Vaghefi, S.A. (2010). Phase II Monitoring of Multivariate simple Linear Profiles. Computers and Industrial Engineering, 58, 563-570.Qui, P., Zou, C., Wang, Z. (2010). Nonparametric profile monitoring by mixed effects modeling. Technometrices, 52, 265-277.Soleimani, P., Noorossana, R., Amiri, A. (2009). Simple Linear Profiles Monitoring in the Presence of Within Profile Autocorrelation. Computers and Industrial Engineering, 57, pp. 1015-1021.Vaghefi, S.A., Tajbakhsh, S.D., Noorossana, R. (2009). Phase II Monitoring of Nonlinear Profiles. Communication in statistics-Theory and Methods, 38, 1834-1851.Williams, J.D., Woodall, W.H., Birch, J.B. (2007). Statistical Monitoring of Nonlinear Product and Process Quality Profiles. Quality and Reliability Engineering International, 23, pp. 925–941.Wodall, W.H., Spitzner, D.J., Montgomery, D.C., Gupta, S. (2004). Using control chart to monitor process and product quality profiles. Journal of Quality Technology, 36, 309-320.Zhang, N. F. (1998). A Statistical Control Chart for Stationary Process Data. Technometrics, 40, 24-38.Zhang, N. F. (2000). Statistical Control Charts for Monitoring the Mean of a Stationary Process. Journal of Statistical Computation & Simulation, 66, 249-258.Zou, C., Tsung, F., Wang, Z. (2008). Technometrics. Monitoring Profiles Based on Nonparametric Regression Methods, 50, 512-526.Zou, C., Zhang, Y., Wang, Z. (2006). Control Chart Based on Change-Point Model for Monitoring Linear Profiles. 38, 1093-1103. 描述 碩士
國立政治大學
統計研究所
100354004
101資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100354004 資料類型 thesis dc.contributor.advisor 楊素芬<br>鄭宗記 zh_TW dc.contributor.author (作者) 王儀茹 zh_TW dc.creator (作者) 王儀茹 zh_TW dc.date (日期) 2012 en_US dc.date.accessioned 2-九月-2013 15:36:09 (UTC+8) - dc.date.available 2-九月-2013 15:36:09 (UTC+8) - dc.date.issued (上傳時間) 2-九月-2013 15:36:09 (UTC+8) - dc.identifier (其他 識別碼) G0100354004 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/59284 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計研究所 zh_TW dc.description (描述) 100354004 zh_TW dc.description (描述) 101 zh_TW dc.description.abstract (摘要) 追蹤季節性時間數列模型之流程資料 zh_TW dc.description.abstract (摘要) Control charts are designed and evaluated under the assumption that the observations from the process are independent and identically distributed. However, the independence assumption is often violated in practice. Autocorrelation may be represented in many processes. To solve this problem, it is becoming more common to obtain profiles at each time period. Profile monitoring is the use of control charts for cases in which the quality of a process or product can be characterized by a functional relationship between a response variable and one or more explanatory variables. For the data with seasonal time series model, we propose several monitoring approaches to detect the out-of-control profiles. After considering both Phase I and Phase II schemes, a real example is given to illustrate the results. en_US dc.description.tableofcontents ContentsChapter 1 Introduction 1Chapter 2 Research Methods 42.1 Control Bands under each time unit 52.1.1 Introduction 52.1.2 Model assumptions and notations 52.2 Confidence bands based on Kalman Filter approach 72.2.1 Introduction 72.2.2 Model assumption and notation 82.2.3 State Space Model 102.2.4 Kalman Filter 122.3 Confidence Bands based on Bootstrap approach 152.3.1 Introduction 152.3.2 Bootstrap Procedure 162.3.3 Control chart for monitoring variance of the residuals 162.4 Hotelling T2 control charts 172.4.1 Introduction 172.4.2 Hotelling’s T2 Control Chart 172.4.3 T2 chart for monitoring coefficients of a profile 182.4.4 T2 chart for monitoring variance of the residuals 19Chapter 3 Real data analysis: Power Consumption in National Chengchi University 213.1 Introduction 213.2 Data classification 223.3 Phase I and Phase II control scheme 303.3.1 Model assumption and identification 303.3.2 Phase I and Phase II control charts 353.3.3 Example of Semester without AC data (WOAC data) 363.3.4 Example of Semester with AC data (WAC data) 443.4 Performance Comparison 52Chapter 4 Conclusions 61References 62 zh_TW dc.format.extent 1460546 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100354004 en_US dc.subject (關鍵詞) 季節性時間數列 zh_TW dc.subject (關鍵詞) 信賴帶 zh_TW dc.subject (關鍵詞) 自我相關製程 zh_TW dc.subject (關鍵詞) Seasonal time series model en_US dc.subject (關鍵詞) Confidence band en_US dc.subject (關鍵詞) Autocorrelated process en_US dc.title (題名) 追蹤季節性時間數列模型之流程資料 zh_TW dc.title (題名) Monitoring process data with seasonal time series model en_US dc.type (資料類型) thesis en 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, 6(1):87-95.Box, G.E.P., Jenkins, G.M.,Reinsel G.C. (2008). Time series Analysis: Forecasting and Control, 4th ed. New York: John Wiley and Sons.Brockwell, P. J. and Davis, R. A. (2009). Time Series: Theory and Methods, 2nd ed. New York: Springer-Verlag.Cheng, T-C and Yang, S-F. (2013). Monitoring Profile Based on a Linear Regression Model with Correlated Errors.Ding, Y., Zeng, L., Zhou, S. (2006). Phase I Analysis for Monitoring Nonlinear Profiles in Manufacturing Processes. Journal of Quality Technology, 38(3), 199–216.Durbin,J.,Koopman, S.J. (2001). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.Eyvazian, M., Noorossana, R., Saghaei, A. & Amiri, A. (2011). Phase II Monitoring of Multivariate Multiple Linear Regression Profiles. Quality and Reliability Engineering International, 27, 281-296.Gupta,S.,Montgomery D.C.,Woodall W.H. (2006). Performance evaluation of two methods for online monitoring of linear calibration profiles. International Journal of Production Research, 44, 1927-1942.Harvey, A. (1989). Forecasting, Structural Time Sereis Models and the Kalman Filter. Cambridge: Cambridge University Press.Jensen, W.A., Birch, J.B., Woodall, W.H. (2008). Monitoring correlation within linear profiles using mixed models. Journal of Quality Technology, 40, 167-183.Jensen,W.A.,Birch, J.B. (2009). Profile monitoring via nonlinear mixed models. Journal of Quality Technology, 41, 18-34.Kang, L., Albin, S.L. (2000). On-Line Monitoring When the Process Yields a Linear Profile. Journal of Quality Technology, 32, 418–426.Kang, L., Albin, S.L. (2000). On-line monitoring when the process yields a linear profile. Journal of Quality Technology, 32, 418-426.Kazemzadeh, R.B., Noorossana, R., Amiri, A. (2008). Phase I Monitoring of Polynomial Profiles. Communications in Statistics-Theory and Methods, 37, 1671-1686.Kim, K., Mahmoud, M.A., Woodall, W.H. (2003). On the Monitoring of Linear Profiles. Journal of Quality Technology, 35, 317–328.Kim, K., Mahmoud, M.A., Woodall, W.H. (2003). On the Monitoring of Linear Profiles. Journal of Quality Technology, 35, 317-328.Lowry, C. A. and Montgomery, D. C. (1995). A Review of Multivariate Control. IIE Transactions, 27, 800-810.Lu, C. W. and Reynolds, M. R., Jr. (1999a). Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes. Journal of Quality Technology, 31, 259-274.Montgomery, D. C. (2005). Introduction to statistical quality control, 5nd edn. John Wiley, New York.Noorossana, R., Eyvazian, M., Amiri, A., Mahmoud, M.A. (n.d.). "Statistical Monitoring of Multivariate Multiple Linear Regression Profiles in Phase I with Calibration Application. Quality and Reliability Engineering International, 26, 291-303.Noorossana, R., Amiri, A., Soleimani, P. (2008). On the Monitoring of Autocorrelated Linear Profiles. Communications in Statistics-Theory and Methods, 37, 425-442.Noorossana, R., Eyvazian, M., Vaghefi, S.A. (2010). Phase II Monitoring of Multivariate simple Linear Profiles. Computers and Industrial Engineering, 58, 563-570.Qui, P., Zou, C., Wang, Z. (2010). Nonparametric profile monitoring by mixed effects modeling. Technometrices, 52, 265-277.Soleimani, P., Noorossana, R., Amiri, A. (2009). Simple Linear Profiles Monitoring in the Presence of Within Profile Autocorrelation. Computers and Industrial Engineering, 57, pp. 1015-1021.Vaghefi, S.A., Tajbakhsh, S.D., Noorossana, R. (2009). Phase II Monitoring of Nonlinear Profiles. Communication in statistics-Theory and Methods, 38, 1834-1851.Williams, J.D., Woodall, W.H., Birch, J.B. (2007). Statistical Monitoring of Nonlinear Product and Process Quality Profiles. Quality and Reliability Engineering International, 23, pp. 925–941.Wodall, W.H., Spitzner, D.J., Montgomery, D.C., Gupta, S. (2004). Using control chart to monitor process and product quality profiles. Journal of Quality Technology, 36, 309-320.Zhang, N. F. (1998). A Statistical Control Chart for Stationary Process Data. Technometrics, 40, 24-38.Zhang, N. F. (2000). Statistical Control Charts for Monitoring the Mean of a Stationary Process. Journal of Statistical Computation & Simulation, 66, 249-258.Zou, C., Tsung, F., Wang, Z. (2008). Technometrics. Monitoring Profiles Based on Nonparametric Regression Methods, 50, 512-526.Zou, C., Zhang, Y., Wang, Z. (2006). Control Chart Based on Change-Point Model for Monitoring Linear Profiles. 38, 1093-1103. zh_TW
