政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/51201
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113392/144379 (79%)
Visitors : 51227285      Online Users : 959
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/51201


    Title: 二元損失管制圖之設計
    Design of the bivariate loss control chart
    Authors: 呂雨築
    Lu, Yu Chu
    Contributors: 楊素芬
    Yang,Su Fen
    呂雨築
    Lu, Yu Chu
    Keywords: 二元損失管制圖
    Date: 2010
    Issue Date: 2011-10-05 14:31:56 (UTC+8)
    Abstract: 利用單一二元損失管制圖來偵測製程平均數向量及共變異數矩陣同時偏移。不同於已存在的多元管制圖,本文所提出的管制圖是以二元平均損失函數建構而成的,因此,在監控製程時,我們同時能獲得產品平均損失的資訊。平均連串長度分析結果指出二元損失管制圖在偵測製程小幅度偏移上有不錯的其偵測能力。本文將與現存的多元方法做績效表現的比較,例如:二元管制圖、多元的累積管制圖和多元的指數加權平均管制圖等。結果顯示,二元損失管制圖在偵測程平均數向量及共變異數矩陣同時偏移的情況下有較好的偵測能力。
    Reference: 1. Alt, F. B. (1985), “Multivariate quality control,” In: Kotz, S. and Johnson, N., eds. Encyclopedia of Statistics. 6, John Wiley & Sons, New York, NY, 110-122.
    2. Alt, F. B. and Bedewi, G. E. (1986), “SPC for dispersion for multivariate data,” ASQC. Qual. Congress Trans, 248-254.
    3. Aparisi F. and Haro, C. L. (2001), “Hotelling T2 control chart with variable sampling intervals,” Int. J. Prod. Res, 39(14), 3127-3140.
    4. Chan, L. K. and Zhang, J. (2001), “Cumulative sum control chart for the covariance matrix,” Statist. Sinica, 11, 767-790.
    5. Chen Y. K. and Hsieh K. L. (2007), “Hotelling T2 control chart with variable sample size and control limit,” European Journal of Operational Research, 182, 1251 – 1262.
    6. Cheng, G. Z. (1995), “A Study of an Application on the Multi-Characteristic Quality Loss Function,” Master’s Thesis, Providence University, Shalu, Taiwan.
    7. Cheng, S. W. and Thaga, K. (2005), ”Multivariate Max-CUSUM chart,” Quality Technology & Quantitative Management, 2(2), 221-235.
    8. Chou, C. Y., Liu, H. R., Chen, C. H. and Huang, X. R. (2002), “Economic-statistical design of multivariate control charts using quality loss function,” Int J Adv Manuf Technol, 20, 916-924.
    9. Costa, A. F. B. and Machado, M. A. G. (2009), “A new chart based on sample variances for monitoring the covariance matrix of multivariate processes,” Int J Adv Manuf Technol, 41, 770-779.
    10. Crosier, R. B. (1988), “Multivariate generalizations of cumolative sum quality control schemes,” Technometrics, 30, 291-303.
    11. Farebrother, R. W. (1984), “Algorithm AS 204: The distribution of a positive linear combination of random variables,” Journal of the Royal Statistical Society, Series C (Applied Statistics), 33, 332-339.
    12. Hawkins, D. M. (1991), “Multivariate quality control based on regression – adjusted variables,” Technometrics, 33, 61-75.
    13. Hawkins, D. M. and Maboudou-Tchao, E. M. (2008), “Multivariate exponentially weighted moving covariance matrix,” Technometrics, 50, 155-166.
    14. Hawkins, D. M., Qiu, P. and Kang, C. W. (2003), “The changepoint model for statistical process control,” Journal of Quality Technology, 35 (4), 355-366.
    15. Hawkins, D. M. and Zamba K. D. (2005), “Statistical process control for shifts in mean or variance using a changepoint formulation,” Technometrics, 47 (2), 164-173.
    16. Healy, J. D. (1987), “A note on multivariate quality CUSUM procedures,” Technometrics, 29, 409-412.
    17. Imhof, J. P. (1961), “Computing the distribution of quadratic forms in normal variables,” Biometrika, 48(3 and 4), 419-426.
    18. Jackson, J. E. (1959), “Quality control methods for several related variables,” Technometrics, 1, 359-377.
    19. James, W. and Stein, C. (1961), “Estimation with quadratic loss,” Fourth Berkeley Simpslum, 361-379.
    20. Johnson, R. A. and Wichern D. W. (1992), “Applied multivariate statistical analysis,” Englewood Cliffs, N.J. : Prentice Hall
    21. Khoo, B. C. (2005), “A new bivariate control chart to monitor the multivariate process mean and variance simultaneously,” Quality Engineering, 17, 109-118.
    22. Liu, H., Tang, Y., and Zhang, H. H. (2009), “Computational statistics and data analysis,” Computational Statistics and Data Analysis, 53, 853-856.
    23. Liu, R. Y. (1995), “Control charts for multivariate process,” J. Amer. Statist. Assoc, 90, 1380-1387.
    24. Lowry, C. A., Woodall, W. H., Champ, C. W. and Rigdon, S. E. (1992), “A multivariate exponentially weighted moving average control chart,” Technometrics, 34, 46-53.
    25. Mahmoud, M. A. and Zahran, A. R. (2011), “ A multivariate adaptive exponentially weighted moving average control chart,” Communications in Statistics – Theory and Methods, 39 (4), 606-625.
    26. Mohebbi, C. and Hayre, L. (1989), “Multivariate control charts: a loss function approach,” Sequential Analysis, 8, 253-268.
    27. Moschopoulous, P. G. and Canada, W. B. (1984), “The distribution function of a linear combination of chi-square,” Comp. & Maths, with Appls., 10, 383-386.
    28. Montgomery, D. C. (2001), Introduction to statistical quality control, 4th Ed, John Wiley & Sons, New York, NY.
    29. Patnaik, P. B. (1949), “The non-central - and F-distribution and their applications,” Biometrika, 36, 202-232.
    30. Pearson, E. S. (1959), “Note on an approximation to the distribution of non-central ,” Biometrika, 46, 364-365.
    31. Pignatiello, J. J. and Runger, G. C. (1990), “Comparisons of multivariate CUSUM charts,” J. Qual. Technol, 22, 173-186.
    32. Qiu, P. and Hawkins, D. M. (2001), “A rank-based multivariate CUSUM procedure,” Technometrics, 43, 120-132.
    33. Reynolds, M. R. and Cho, G. Y. (2006), “Multivariate control charts for monitoring the mean vector and covariance matrix,” J. Qual. Technol, 38(3), 230-253.
    34. Spiring, F. A. and Cheng, S. W. (1998), “An alternate variables control chart: the univariate and multivariate case,” Statistica Sinica, 8, 273-287.
    35. Stoumbos, Z. G., Reynolds, M. R., Ryan, T. P. and Woodall, W. H. (2000). “The state of statistical process control as we proceed into the 21st century,” J. Amer. Statist. Assoc, 95, 992-998.
    36. Tang, P. F. and Barnett, N. S. (1996a), “Dispersion control for multivariate processes,” Aust. N. J. Stat, 38, 235-251.
    37. Tang, P. F. and Barnett, N. S. (1996b), “Dispersion control for multivariate processes-some comparisons,” Aust. N. J. Stat, 31, 376-386.
    38. Tsui, K. and Woodall, W. H. (1993), “Multivariate control charts based on loss functions,” Sequential Analysis, 12(1), 79-92.
    39. Woodall, W. H. and Montgomery D. C. (1999), “Research issues and ideas in statistical process control,” J. Qual. Technol, 31, 376-386.
    40. Woodall, W. H. and Nucube, M. M. (1985), “Multivariate CUSUM quality control procedures,” Technometrics, 27, 285-292.
    41. Xie, H. (1999). “Contribution to qualimetry,” Ph.D. thesis, University of Manitoba, Winnipeg, Canada.
    42. Yang, S. F., Lin, K. J. and Hung, T.C. (2009), “ Improvement in consistency of the metallic film thickness of computer connectors,” Journal of Process Control, 19, 498-505.
    43. Yeh, A. B., Huwang, L. and Wu, Y. F. (2004), “A likelihood-ratio-based EWMA control chart for monitoring variability of multivariate normal processes,” IIE Trans, 36, 865-879.
    44. Yeh, A. B., Huwang, L. and Wu, C. W. (2005), “A multivariate EWMA control chart for monitoring process variability with individual observations,” IIE Trans, 37, 1023-1035.
    45. Yeh, A. B. and Lin, D. K. (2002), “A new variables control chart for simultaneously monitoring multivariate process mean and variability,” Int. J. Reliab. Qual. Saf. Eng, 9 (1). 41-59.
    46. Yeh, A. B., Lin, K. J., Zhou, H. H. and Venkataramani, C. (2003), “ A multivariate exponentially weighted moving average control chart for monitoring process variability,” Journal of Applied Statistics, 30(5), 507-536.
    47. Zamba, K. D. and Hawkinsm D. M. (2006), “A multivariate change-point model for statistical process control,” Technometrics, 48 (4), 539-548.
    48. Zhang, J., Li, Z. and Wang, Z. (2010), “A multivariate control chart for simultaneously monitoring process mean and variability,” Computational Statisitcs and Data Analysis, 54, 2244-2252.
    Description: 碩士
    國立政治大學
    統計研究所
    98354004
    99
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0098354004
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

    Files in This Item:

    File SizeFormat
    400401.pdf1407KbAdobe PDF21047View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback