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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/139853


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/139853


    Title: A Phase II Depth-Based Variable Dimension EWMA Control Chart for Monitoring Process Mean
    Authors: 楊素芬
    Yang, Su-Fen
    Lin, Yi-Chi
    Yeh, Arthur B.
    Contributors: 統計系
    Keywords: data depth;exponentially weighted moving average;Phase II monitoring;variable dimension
    Date: 2021-10
    Issue Date: 2022-04-12
    Abstract: Statistical process control consists of tools and techniques that are useful for improving a process or ensuring that a process is in a stable and satisfactory state. In many modern industrial applications, it is critically important to simultaneously monitor two or more correlated process quality variables, thus necessitating the development of multivariate statistical process control (MSPC) as an important area of research for the new century. Nevertheless, the existing MSPC research is mostly based on the assumption that the process data follow a multinormal distribution or a known distribution. However, it is well recognized that in many applications the underlying process distribution is unknown. In practice, among a set of correlated variables to be monitored, there is oftentimes a subset of variables that are easy and/or inexpensive to measure, whereas the remaining variables are difficult and/or expensive to measure but contain information that may help more quickly detect a shift in the process mean. We are motivated to develop a Phase II control chart to monitor variable dimension (VD) mean vector for unknown multivariate processes. The proposed chart is based on the exponentially weighted moving average (EWMA) of a depth-based statistic. The proposed chart is shown to lead to faster detection of mean shifts than the existing VDT2 and VD EWMAT2 charts studied in Aparisi et al. and Epprecht et al., respectively.
    Relation: Quality and Reliability International, Vol.37, No.6, pp.2384-2398
    Data Type: article
    DOI 連結: https://doi.org/10.1002/qre.2863
    DOI: 10.1002/qre.2863
    Appears in Collections:[統計學系] 期刊論文

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