Linear profiles monitoring in the presence of nonnormal random errors

Chung I. Li, Tzong Ru Tsai

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

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.

原文English
頁(從 - 到)2579-2592
頁數14
期刊Quality and Reliability Engineering International
35
發行號8
DOIs
出版狀態Published - 2019 十二月 1

All Science Journal Classification (ASJC) codes

  • 安全、風險、可靠性和品質
  • 管理科學與經營研究

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