A double generally weighted moving average control chart for monitoring the process variability
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
| Publié dans: | Journal of applied statistics. - 1991. - 50(2023), 10 vom: 15., Seite 2079-2107 |
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| Auteur principal: | |
| Autres auteurs: | , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2023
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| Accès à la collection: | Journal of applied statistics |
| Sujets: | Journal Article Average run-length control chart double generally weighted moving average logarithmic transformation process variability |
| Résumé: | © 2022 Informa UK Limited, trading as Taylor & Francis Group. In the present article, a double generally weighted moving average (DGWMA) control chart based on a three-parameter logarithmic transformation is proposed for monitoring the process variability, namely the S2-DGWMA chart. Monte-Carlo simulations are utilized in order to evaluate the run-length performance of the S2-DGWMA chart. In addition, a detailed comparative study is conducted to compare the performance of the S2-DGWMA chart with several well-known memory-type control charts in the literature. The comparisons indicate that the proposed one is more efficient in detecting small shifts, while it is more sensitive in identifying upward shifts in the process variability. A real data example is given to present the implementation of the new S2-DGWMA chart |
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| Description: | Date Revised 21.09.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
| ISSN: | 0266-4763 |
| DOI: | 10.1080/02664763.2022.2064977 |