Premium
A Comparison of Shewhart Individuals Control Charts Based on Normal, Non‐parametric, and Extreme‐value Theory
Author(s) -
Vermaat M. B. Thijs,
Ion Roxana A.,
Does Ronald J. M. M.,
Klaassen Chris A. J.
Publication year - 2003
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.586
Subject(s) - control chart , quantile , estimator , normality , parametric statistics , extreme value theory , statistics , mathematics , econometrics , shewhart individuals control chart , computer science , ewma chart , process (computing) , operating system
Abstract Several control charts for individual observations are compared. Traditional ones are the well‐known Shewhart individuals control charts based on moving ranges. Alternative ones are non‐parametric control charts based on empirical quantiles, on kernel estimators, and on extreme‐value theory. Their in‐control and out‐of‐control performance are studied by simulation combined with computation. It turns out that the alternative control charts are not only quite robust against deviations from normality but also perform reasonably well under normality of the observations. The performance of the Empirical Quantile control chart is excellent for all distributions considered, if the Phase I sample is sufficiently large. Copyright © 2003 John Wiley & Sons, Ltd.