On ARL-unbiased control charts
Publication date
2015-04-24
Document type
Konferenzbeitrag
Author
Morais, Manuel Cabral
Organisational unit
Conference
11th International Workshop on Intelligent Statistical Quality Control ; Sydney, Australia ; August 20–23, 2013
Publisher
Springer
Series or journal
Periodical volume
11
Book title
Frontiers in statistical quality control 11
First page
95
Last page
117
Part of the university bibliography
✅
Language
English
Keyword
Power function
Run length
Statistical process control
Abstract
Manufacturing processes are usually monitored by making use of control charts for variables or attributes. Controlling both increases and decreases in a parameter, by using a control statistic with an asymmetrical distribution, frequently leads to an ARL-biased chart, in the sense that some out-of-control average run length (ARL) values are larger than the in-control ARL, i.e., it takes longer to detect some shifts in the parameter than to trigger a false alarm. In this paper, we are going to: explore what Pignatiello et al. (4th Industrial Engineering Research Conference, 1995) and Acosta-Mejía et al. (J Qual Technol 32:89-102, 2000) aptly called an ARL-unbiased chart; provide instructive illustrations of ARL-(un)biased charts of the Shewhart-, exponentially weighted moving average (EWMA)-, and cumulative sum (CUSUM) type; relate ARL-unbiased Shewhart charts with the notions of unbiased and uniformly most powerful unbiased (UMPU) tests; briefly discuss the design of EWMA charts not based on ARL(-unbiasedness).
Version
Published version
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