English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51726142      Online Users : 633
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
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/140179


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/140179


    Title: A New Phase II EWMA Dispersion Control Chart
    Authors: 楊素芬
    Yang, Su-Fen
    Arnold, Barry C.;Liu, Yen-ling;Lu, Ming-Che;Lu, Shin-Li
    Contributors: 統計系
    Keywords: average run length;dispersion control chart;multivariate distribution;variance covariance matrix
    Date: 2021-12
    Issue Date: 2022-05-30 16:02:37 (UTC+8)
    Abstract: Statistical process control (SPC) methods are useful for improving or maintaining a manufacturing or service process in a stable and satisfactory state. Nowadays, in many industrial applications, it is necessary to simultaneously monitor more than two related quality variables of a process. Multivariate control charts are thus becoming an important research area. Using separate control charts to monitor related quality variables independently is very unreasonable and misleading. The problem of monitoring multivariate statistical process (MSPC) for several related quality variables is of current interest. So far in the literature, a few papers have discussed monitoring process dispersion for cases in which the process has a multivariate normal or non-normal distribution. A new EWMA dispersion control chart is proposed to monitor the process covariance matrix. Moreover, the proposed new EWMA dispersion control chart is independent of the out-of-control process mean vector. It overcomes the problem in many existing covariance matrix control charts of assuming that there are no shifts in the process mean vector which, depending on the existence of shifts in mean, can lead to an increased false alarm rate. The derivation of the new EWMA dispersion control chart is illustrated and its out-of-control detection performance investigated. The proposed new EWMA dispersion control chart performs better than the existing control charts for detecting out-of-control process variances whether the covariances change or not. An example involving semi-conductor data is adopted to demonstrate the application of the proposed new EWMA dispersion control chart.
    Relation: Quality and Reliability Engineering Internationa, 38(4), 1635-1658
    Data Type: article
    DOI 連結: https://doi.org/10.1002/qre.3039
    DOI: 10.1002/qre.3039
    Appears in Collections:[統計學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML2208View/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