Some Recent Developments on the Effects of Parameter Estimation on Control Charts

Psarakis, Stelios; Vyniou, Angeliki K.; Castagliola, Philippe

doi:10.1002/qre.1556

Cited by 153 publications

(98 citation statements)

References 80 publications

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“…For two reviews on this topic, see Jensen et al (2006) and Psarakis, Vyniou, and Castagliola (2014). The general conclusion is that the use of parameter estimates results in control charts with less predictable performance than those with known parameters.…”

Section: Introductionmentioning

confidence: 99%

A head-to-head comparative study of the conditional performance of control charts based on estimated parameters

Zwetsloot

Woodall

2016

Quality Engineering

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General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. ABSTRACTImplementation of the Shewhart, CUSUM, and EWMA charts requires estimates of the in-control process parameters. Many researchers have shown that estimation error strongly influences the performance of these charts. However, a given amount of estimation error may differ in effect across charts. Therefore, we perform a pairwise comparison of the effect of estimation error across these charts. We conclude that the Shewhart chart is more strongly affected by estimation error than the CUSUM and EWMA charts. Furthermore, we show that the general belief that the CUSUM and EWMA charts have similar performance no longer holds under estimated parameters.

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Section: Introductionmentioning

confidence: 99%

A head-to-head comparative study of the conditional performance of control charts based on estimated parameters

Zwetsloot

Woodall

2016

Quality Engineering

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“…This variation in control chart performance has been addressed by several researchers, and is of great interest in current SPC literature. An overview of this literature is given by Jensen et al (2006) and Psarakis, Vyniou, and Castagliola (2014).…”

Section: Introductionmentioning

confidence: 99%

Correction factors for Shewhart and control charts to achieve desired unconditional ARL

Goedhart

Schoonhoven

Does

2016

International Journal of Production Research

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In this paper we derive correction factors for Shewhart control charts that monitor individual observations as well as subgroup averages. In practice, the distribution parameters of the process characteristic of interest are unknown and, therefore, have to be estimated. A well-known performance measure within Statistical Process Monitoring is the expectation of the average run length (ARL), defined as the unconditional ARL. A practitioner may want to design a control chart such that, in the in-control situation, it has a certain expected ARL. However, accurate correction factors that lead to such an unconditional ARL are not yet available. We derive correction factors that guarantee a certain unconditional in-control ARL. We use approximations to derive the factors and show their accuracy and the performance of the control charts -based on the new factors -in out-of-control situations. We also evaluate the variation between the ARLs of the individually estimated control charts.

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“…And it has an influence on the performance of the control chart seriously due to the variability of the estimators (Jensen, Jones-Farmer, Champ, & Woodall, 2006;Psarakis, Vyniou, & Castagliola, 2013;Quesenberry, 1993;Woodall & Montgomery, 2014). The results in Section 3 show that the influence of estimated parameter for the proposed chart is serious.…”

Section: Introductionmentioning

confidence: 94%

Optimal design of a synthetic chart for monitoring process dispersion with unknown in-control variance

Guo

Wang

Cheng

2015

Computers & Industrial Engineering

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Some Recent Developments on the Effects of Parameter Estimation on Control Charts

Abstract: International audienc

Cited by 153 publications

References 80 publications

A head-to-head comparative study of the conditional performance of control charts based on estimated parameters

A head-to-head comparative study of the conditional performance of control charts based on estimated parameters

Correction factors for Shewhart and control charts to achieve desired unconditional ARL

Optimal design of a synthetic chart for monitoring process dispersion with unknown in-control variance

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