Run length quantiles of EWMA control charts monitoring normal mean or/and variance
Publication date
2015-02-03
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Taylor & Francis
Series or journal
International Journal of Production Research
ISSN
Periodical volume
53
Periodical issue
15
First page
4629
Last page
4647
Part of the university bibliography
✅
Language
English
Keyword
average run length
false alarm probability
fast initial response
median run length
numerical methods
quality control
time-varying control limits
Abstract
Exponentially weighted moving average (EWMA) control charts are well-established devices for monitoring process stability. Typically, control charts are evaluated by considering their Average Run Length (ARL), that is the expected number of observations or samples until the chart signals. Because of the limitations of an average, various papers also dealt with the run length distribution and quantiles. Going beyond these papers, we develop algorithms for and evaluate the quantile performance of EWMA control charts with variance adjusted control limits and with fast initial response features, of EWMA charts based on the sample variance, and of EWMA charts simultaneously monitoring mean and variance. Additionally, for the mean charts we consider medium, late and very late process changes and their impact on appropriately conditioned run length quantiles. It is demonstrated that considering run length quantiles can protect from constructing distorted EWMA designs while optimising their zero-state ARL performance. The implementation of all the considered measures in the R package 'spc' allows any control chart user to consider EWMA schemes from the run length quantile prospective in an easy way.
Version
Published version
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Metadata only access