An adaptive max-type multivariate control chart by considering measurement errors and autocorrelation
Sabahno, Hamed LU
(2023)
In Journal of Statistical Computation and Simulation
93(16).
p.2956-2981
- Abstract
The combined effect of two real-world-occurring phenomena: ‘measurement errors’ and ‘autocorrelation between observations’ has rarely been investigated. In this paper, it will be investigated for the first time on ‘adaptive’ and/or ’simultaneous monitoring’ charts and also for the first time by using the multivariate linearly covariate measurement errors and VARMA (vector mixed autoregressive and moving average) autocorrelation models, and Markov chains-based performance measures. In addition, this paper for the first time proposes a skip-sampling strategy in an ARMA/VARMA model for alleviating the autocorrelation effect. To do so, we add the above-mentioned measurement errors and autocorrelation models to a recently developed adaptive... (More)
The combined effect of two real-world-occurring phenomena: ‘measurement errors’ and ‘autocorrelation between observations’ has rarely been investigated. In this paper, it will be investigated for the first time on ‘adaptive’ and/or ’simultaneous monitoring’ charts and also for the first time by using the multivariate linearly covariate measurement errors and VARMA (vector mixed autoregressive and moving average) autocorrelation models, and Markov chains-based performance measures. In addition, this paper for the first time proposes a skip-sampling strategy in an ARMA/VARMA model for alleviating the autocorrelation effect. To do so, we add the above-mentioned measurement errors and autocorrelation models to a recently developed adaptive max-type chart. Then, we develop a Markov chain model to compute the performance measures. After that, extensive numerical analyses will be performed to investigate their combined effect as well as some methods to alleviate their negative effects. Finally, an illustrative example involving a real industrial case will be presented.
(Less)
- author
- Sabahno, Hamed
LU
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- adaptive control charts, autocorrelation, Markov chains, max-type control charts, measurement errors, Multivariate control charts
- in
- Journal of Statistical Computation and Simulation
- volume
- 93
- issue
- 16
- pages
- 26 pages
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:85161574037
- ISSN
- 0094-9655
- DOI
- 10.1080/00949655.2023.2214830
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
- id
- 7f00e09e-b243-487e-9e80-b7253466c50c
- date added to LUP
- 2025-03-20 12:12:26
- date last changed
- 2025-04-04 14:24:39
@article{7f00e09e-b243-487e-9e80-b7253466c50c,
abstract = {{<p>The combined effect of two real-world-occurring phenomena: ‘measurement errors’ and ‘autocorrelation between observations’ has rarely been investigated. In this paper, it will be investigated for the first time on ‘adaptive’ and/or ’simultaneous monitoring’ charts and also for the first time by using the multivariate linearly covariate measurement errors and VARMA (vector mixed autoregressive and moving average) autocorrelation models, and Markov chains-based performance measures. In addition, this paper for the first time proposes a skip-sampling strategy in an ARMA/VARMA model for alleviating the autocorrelation effect. To do so, we add the above-mentioned measurement errors and autocorrelation models to a recently developed adaptive max-type chart. Then, we develop a Markov chain model to compute the performance measures. After that, extensive numerical analyses will be performed to investigate their combined effect as well as some methods to alleviate their negative effects. Finally, an illustrative example involving a real industrial case will be presented.</p>}},
author = {{Sabahno, Hamed}},
issn = {{0094-9655}},
keywords = {{adaptive control charts; autocorrelation; Markov chains; max-type control charts; measurement errors; Multivariate control charts}},
language = {{eng}},
number = {{16}},
pages = {{2956--2981}},
publisher = {{Taylor & Francis}},
series = {{Journal of Statistical Computation and Simulation}},
title = {{An adaptive max-type multivariate control chart by considering measurement errors and autocorrelation}},
url = {{http://dx.doi.org/10.1080/00949655.2023.2214830}},
doi = {{10.1080/00949655.2023.2214830}},
volume = {{93}},
year = {{2023}},
}