Monitoring non-parametric profiles using adaptive EWMA control chart

<p dir="ltr">To monitor the quality of a process in statistical process control (SPC), considering a functional relationship between a dependent variable and one or more independent variables (which is denoted as profile monitoring) is becoming an increasingly common approach. Most o...

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Main Author: Saddam Akber Abbasi (7908302) (author)
Other Authors: Ali Yeganeh (16624998) (author), Sandile C. Shongwe (10099044) (author)
Published: 2022
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author Saddam Akber Abbasi (7908302)
author2 Ali Yeganeh (16624998)
Sandile C. Shongwe (10099044)
author2_role author
author
author_facet Saddam Akber Abbasi (7908302)
Ali Yeganeh (16624998)
Sandile C. Shongwe (10099044)
author_role author
dc.creator.none.fl_str_mv Saddam Akber Abbasi (7908302)
Ali Yeganeh (16624998)
Sandile C. Shongwe (10099044)
dc.date.none.fl_str_mv 2022-08-22T09:00:00Z
dc.identifier.none.fl_str_mv 10.1038/s41598-022-18381-8
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Monitoring_non-parametric_profiles_using_adaptive_EWMA_control_chart/29069615
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Chemical engineering
Mathematical sciences
Statistics
Statistical process control (SPC)
Profile monitoring
Non-parametric control charts
Adaptive control chart
Regression profile monitoring
dc.title.none.fl_str_mv Monitoring non-parametric profiles using adaptive EWMA control chart
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">To monitor the quality of a process in statistical process control (SPC), considering a functional relationship between a dependent variable and one or more independent variables (which is denoted as profile monitoring) is becoming an increasingly common approach. Most of the studies in the SPC literature considered parametric approaches in which the functional relationship has the same form in the in-control (IC) and out-of-control (OC) situations. Non-parametric profiles, which have a different functional relationship in the OC conditions are very common. This paper designs a novel control chart to monitor not only the regression parameters but also the variation of the profiles in Phase II applications using an adaptive approach. Adaptive control charts adjust the final statistic with regard to information of the previous samples. The proposed method considers the relative distance of the chart statistic to the control limits as a tendency index and provides some outcomes about the process condition. The results of Monte Carlo simulations show the superiority of the proposed monitoring scheme in comparison with the common non-parametric control charts.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41598-022-18381-8" target="_blank">https://dx.doi.org/10.1038/s41598-022-18381-8</a></p>
eu_rights_str_mv openAccess
id Manara2_bc5772f93fcffe749cee62cc99a98c4a
identifier_str_mv 10.1038/s41598-022-18381-8
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/29069615
publishDate 2022
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rights_invalid_str_mv CC BY 4.0
spelling Monitoring non-parametric profiles using adaptive EWMA control chartSaddam Akber Abbasi (7908302)Ali Yeganeh (16624998)Sandile C. Shongwe (10099044)EngineeringChemical engineeringMathematical sciencesStatisticsStatistical process control (SPC)Profile monitoringNon-parametric control chartsAdaptive control chartRegression profile monitoring<p dir="ltr">To monitor the quality of a process in statistical process control (SPC), considering a functional relationship between a dependent variable and one or more independent variables (which is denoted as profile monitoring) is becoming an increasingly common approach. Most of the studies in the SPC literature considered parametric approaches in which the functional relationship has the same form in the in-control (IC) and out-of-control (OC) situations. Non-parametric profiles, which have a different functional relationship in the OC conditions are very common. This paper designs a novel control chart to monitor not only the regression parameters but also the variation of the profiles in Phase II applications using an adaptive approach. Adaptive control charts adjust the final statistic with regard to information of the previous samples. The proposed method considers the relative distance of the chart statistic to the control limits as a tendency index and provides some outcomes about the process condition. The results of Monte Carlo simulations show the superiority of the proposed monitoring scheme in comparison with the common non-parametric control charts.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41598-022-18381-8" target="_blank">https://dx.doi.org/10.1038/s41598-022-18381-8</a></p>2022-08-22T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/s41598-022-18381-8https://figshare.com/articles/journal_contribution/Monitoring_non-parametric_profiles_using_adaptive_EWMA_control_chart/29069615CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/290696152022-08-22T09:00:00Z
spellingShingle Monitoring non-parametric profiles using adaptive EWMA control chart
Saddam Akber Abbasi (7908302)
Engineering
Chemical engineering
Mathematical sciences
Statistics
Statistical process control (SPC)
Profile monitoring
Non-parametric control charts
Adaptive control chart
Regression profile monitoring
status_str publishedVersion
title Monitoring non-parametric profiles using adaptive EWMA control chart
title_full Monitoring non-parametric profiles using adaptive EWMA control chart
title_fullStr Monitoring non-parametric profiles using adaptive EWMA control chart
title_full_unstemmed Monitoring non-parametric profiles using adaptive EWMA control chart
title_short Monitoring non-parametric profiles using adaptive EWMA control chart
title_sort Monitoring non-parametric profiles using adaptive EWMA control chart
topic Engineering
Chemical engineering
Mathematical sciences
Statistics
Statistical process control (SPC)
Profile monitoring
Non-parametric control charts
Adaptive control chart
Regression profile monitoring