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    Title: 追蹤季節性時間數列模型之流程資料
    Monitoring process data with seasonal time series model
    Authors: 王儀茹
    Contributors: 楊素芬
    鄭宗記

    王儀茹
    Keywords: 季節性時間數列
    信賴帶
    自我相關製程
    Seasonal time series model
    Confidence band
    Autocorrelated process
    Date: 2012
    Issue Date: 2013-09-02 15:36:09 (UTC+8)
    Abstract: 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.
    Reference: 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.
    Description: 碩士
    國立政治大學
    統計研究所
    100354004
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0100354004
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

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