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A robust design for the omnibus SPRT control chart under skewed data distributions

Control charts are widely used in manufacturing industries to ensure that production levels are stable and satisfactory. Recently, the omnibus sequential probability ratio test (OSPRT) control chart was developed for the purpose of monitoring the mean and variability of a process simultaneously. As...

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Main Authors: Jing, Wei Teoh, Wei, Lin Teoh, Zhi, Lin Chong, Ming, Ha Lee, Khai, Wah Khaw
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2024
Online Access:http://journalarticle.ukm.my/24131/1/SME%2017.pdf
http://journalarticle.ukm.my/24131/
https://www.ukm.my/jsm/english_journals/vol53num6_2024/contentsVol53num6_2024.html
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spelling my-ukm.journal.241312024-09-06T00:41:47Z http://journalarticle.ukm.my/24131/ A robust design for the omnibus SPRT control chart under skewed data distributions Jing, Wei Teoh Wei, Lin Teoh Zhi, Lin Chong Ming, Ha Lee Khai, Wah Khaw Control charts are widely used in manufacturing industries to ensure that production levels are stable and satisfactory. Recently, the omnibus sequential probability ratio test (OSPRT) control chart was developed for the purpose of monitoring the mean and variability of a process simultaneously. As the OSPRT chart was proposed for the first time in literature, its development relied entirely on the assumption that data follow the Normal distribution. Nonetheless, researchers are frequently reminded that the quality characteristics of manufacturing processes do not necessarily follow the Normal distribution, e.g., strengths of glass fibres, and lifetimes of products. In this paper, we investigate the extent to which the performances of the OSPRT chart designed for the Normal model deteriorate, in situations where the data distributions are Gamma and Lognormal. Results show that the in-control average run length (ARL) and standard deviation of the run length of the OSPRT chart designed for the Normal distribution deteriorate rapidly as skewness increases. To address this issue, we propose a robust design for the OSPRT chart by adjusting its control limits, known as the skewness correction method. It is shown that the skewness-corrected OSPRT chart enjoys a guaranteed in-control ARL, with a justifiable degradation in its out-of-control performances. Besides, we also show some insights into selecting the charting parameters for the skewness-corrected OSPRT chart in order to achieve an optimum out-of-control ARL performance over various shift sizes. The paper wraps up with an illustrative example of the skewness-corrected OSPRT chart for monitoring the weights of radial tyres. Penerbit Universiti Kebangsaan Malaysia 2024 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/24131/1/SME%2017.pdf Jing, Wei Teoh and Wei, Lin Teoh and Zhi, Lin Chong and Ming, Ha Lee and Khai, Wah Khaw (2024) A robust design for the omnibus SPRT control chart under skewed data distributions. Sains Malaysiana, 53 (6). pp. 1441-1461. ISSN 0126-6039 https://www.ukm.my/jsm/english_journals/vol53num6_2024/contentsVol53num6_2024.html
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Control charts are widely used in manufacturing industries to ensure that production levels are stable and satisfactory. Recently, the omnibus sequential probability ratio test (OSPRT) control chart was developed for the purpose of monitoring the mean and variability of a process simultaneously. As the OSPRT chart was proposed for the first time in literature, its development relied entirely on the assumption that data follow the Normal distribution. Nonetheless, researchers are frequently reminded that the quality characteristics of manufacturing processes do not necessarily follow the Normal distribution, e.g., strengths of glass fibres, and lifetimes of products. In this paper, we investigate the extent to which the performances of the OSPRT chart designed for the Normal model deteriorate, in situations where the data distributions are Gamma and Lognormal. Results show that the in-control average run length (ARL) and standard deviation of the run length of the OSPRT chart designed for the Normal distribution deteriorate rapidly as skewness increases. To address this issue, we propose a robust design for the OSPRT chart by adjusting its control limits, known as the skewness correction method. It is shown that the skewness-corrected OSPRT chart enjoys a guaranteed in-control ARL, with a justifiable degradation in its out-of-control performances. Besides, we also show some insights into selecting the charting parameters for the skewness-corrected OSPRT chart in order to achieve an optimum out-of-control ARL performance over various shift sizes. The paper wraps up with an illustrative example of the skewness-corrected OSPRT chart for monitoring the weights of radial tyres.
format Article
author Jing, Wei Teoh
Wei, Lin Teoh
Zhi, Lin Chong
Ming, Ha Lee
Khai, Wah Khaw
spellingShingle Jing, Wei Teoh
Wei, Lin Teoh
Zhi, Lin Chong
Ming, Ha Lee
Khai, Wah Khaw
A robust design for the omnibus SPRT control chart under skewed data distributions
author_facet Jing, Wei Teoh
Wei, Lin Teoh
Zhi, Lin Chong
Ming, Ha Lee
Khai, Wah Khaw
author_sort Jing, Wei Teoh
title A robust design for the omnibus SPRT control chart under skewed data distributions
title_short A robust design for the omnibus SPRT control chart under skewed data distributions
title_full A robust design for the omnibus SPRT control chart under skewed data distributions
title_fullStr A robust design for the omnibus SPRT control chart under skewed data distributions
title_full_unstemmed A robust design for the omnibus SPRT control chart under skewed data distributions
title_sort robust design for the omnibus sprt control chart under skewed data distributions
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2024
url http://journalarticle.ukm.my/24131/1/SME%2017.pdf
http://journalarticle.ukm.my/24131/
https://www.ukm.my/jsm/english_journals/vol53num6_2024/contentsVol53num6_2024.html
_version_ 1811683409434509312
score 13.211869

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