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The variable sampling rate X̄ control charts for monitoring autocorrelated processes
Author(s) -
Lin YuChang,
Chou ChaoYu
Publication year - 2008
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.927
Subject(s) - control chart , autocorrelation , statistics , \bar x and r chart , statistical process control , x bar chart , chart , shewhart individuals control chart , sampling (signal processing) , sampling interval , sample size determination , mathematics , variable (mathematics) , ewma chart , process (computing) , computer science , mathematical analysis , filter (signal processing) , computer vision , operating system
Recent studies demonstrated that the adaptive X̄ control charts are more efficient than fixed parmeters (FP) X̄ control chart from statistical and economic criteria. The usual assumption for designing a control chart is that the observations from the process are independent. However, for many processes, such as chemical processes, consecutive measurements are often highly correlated, especially when the interval between samples is small. In the present paper, the observations are modeled as an AR(1) process plus a random error, and the properties of the variable sampling rate (VSR) X̄ charts are evaluated and studied under this model. Based on the study, the VSR X̄ chart is faster than the FP, variable sampling interval and variable sample size X̄ control charts in detecting mean shifts. However, when the level of autocorrelation is high or the process mean shift is large, the advantage of the VSR X̄ chart is reduced. Copyright © 2008 John Wiley & Sons, Ltd.