淡江大學機構典藏:Item 987654321/117007
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/117007


    Title: Linear profiles monitoring in the presence of nonnormal random errors
    Authors: Li, Chung‐I;TsaI, Tzong‐Ru
    Keywords: EWMA;chart generalized likelihood ratio test;linear profile;Shewhart‐type residual chart;skew normal distribution
    Date: 2019-07-23
    Issue Date: 2019-09-17 12:11:29 (UTC+8)
    Publisher: John Wiley & Sons
    Abstract: Profile monitoring is a technique to test the stability of the relationship between a response variable and explanatory variables over time. The most relevant linear profile monitoring methods have been constructed using the normality assumption. However, the normality assumption could be violated in many quality control applications. In this study, we consider a situation in which the random errors in a linear profile model follow a skew‐normal distribution. The skew‐normal distribution is a generalized version of the normal distribution. A new Shewhart‐type chart and exponentially weighted moving average (EWMA) chart, named the ShewhartR and EWMAR charts, respectively, are constructed based on residuals to monitor the parameters of linear profile model. The simulation results show that the multivariate EWMA chart is sensitive to the normality assumption and that the proposed ShewhartR and EWMAR charts have good ability to detect big and small‐to‐moderate process shifts, respectively. An example using photo mask techniques in semiconductor manufacturing is provided to illustrate the applications of the ShewhartR and EWMAR charts.
    Relation: Quality and Reliability Engineering International 2019, p.1-14
    DOI: 10.1002/qre.2543
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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