Linear profiles monitoring in the presence of nonnormal random errors

doi:10.1002/qre.2543

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/117007

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题名:	Linear profiles monitoring in the presence of nonnormal random errors
作者:	Li, Chung‐I;TsaI, Tzong‐Ru
关键词:	EWMA;chart generalized likelihood ratio test;linear profile;Shewhart‐type residual chart;skew normal distribution
日期:	2019-07-23
上传时间:	2019-09-17 12:11:29 (UTC+8)
出版者:	John Wiley & Sons
摘要:	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.
關聯:	Quality and Reliability Engineering International 2019, p.1-14
DOI:	10.1002/qre.2543
显示于类别:	[統計學系暨研究所] 期刊論文

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