A further note on the exponentially weighted moving average control charts for monitoring gradual shifts in a process mean

被引:1
作者
Maghsoodloo, Saeed [1 ]
Silva, Daniel F. [1 ]
机构
[1] Auburn Univ, ISE Dept, Auburn, AL 36849 USA
关键词
autocorrelation function; average run length; bivariate normal density; exponentially weighted moving averages;
D O I
10.1002/qre.3197
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article provides a historical discussion of exponentially weighted moving average (EWMA) control charts and makes minor modifications. Because the charting statistics are correlated, both the autocovariance and autocorrelations functions are derived; it is determined that the steady-state autocorrelation also diminishes geometrically. Assuming normality of individual observations, two successive EWMA statistics have the bivariate normal distribution with an autocorrelation of lag 1. We then used the bivariate normal density to approximate the type II error probability, thereby obtaining the first-order conditional average run length.
引用
收藏
页码:4182 / 4195
页数:14
相关论文
共 9 条
[2]  
DeVor RE., 2007, STAT QUALITY DESIGN, P305
[3]  
Grant EL., 1996, STAT QUALITY CONTROL, P386
[4]  
Johnson R. A., 2007, Applied multivariate statistical analysis
[5]  
LUCAS JM, 1990, TECHNOMETRICS, V32, P1, DOI 10.2307/1269835
[6]  
Mitra A., 2021, Fundamentals of Quality Control and Improvement, V5th
[7]  
Montgomery DC., 2020, INTRO STAT QUALITY C, P390
[8]  
Roberts SW., 1959, Technometrics, V1, P239, DOI [DOI 10.1080/00401706.1959.10489860, 10.1080/00401706.1959.10489860, DOI 10.2307/1266443]
[9]   CONTROL CHARTS USING COUPLED EXPONENTIALLY WEIGHTED MOVING AVERAGES [J].
SWEET, AL .
IIE TRANSACTIONS, 1986, 18 (01) :26-33