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Exponentially weighted moving average—Moving average charts for monitoring the process mean
This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving Average—Moving Average Chart (EWMA-MA) to detect the mean change in a process underlying symmetric and asymmetric distributions. The performance of the proposed control chart are compared with Shewhar...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7021313/ https://www.ncbi.nlm.nih.gov/pubmed/32059001 http://dx.doi.org/10.1371/journal.pone.0228208 |
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author | Sukparungsee, Saowanit Areepong, Yupaporn Taboran, Rattikarn |
author_facet | Sukparungsee, Saowanit Areepong, Yupaporn Taboran, Rattikarn |
author_sort | Sukparungsee, Saowanit |
collection | PubMed |
description | This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving Average—Moving Average Chart (EWMA-MA) to detect the mean change in a process underlying symmetric and asymmetric distributions. The performance of the proposed control chart are compared with Shewhart, MA, EWMA, MA-EWMA and EWMA-MA control charts by using average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) as the criteria for measuring efficiency which evaluated by using Monte Carlo simulation (MC), Moreover, the proposed control chart will be applied to real data. The results of performance comparison showed that the presented control charts performed better detection than the Shewhart, MA, and EWMA charts. However, the results of detection tended to be slower than those for the MA-EWMA chart. The value of ARL(1) for the mixed control chart depends on the parameters of the statistics for such control chart. The EWMA-MA chart is a variable following λ and the MA-EWMA chart is varied according to w. From applying the proposed control chart to the data for flow in the Nile River and data of the real GDP growth (%) in the Lebanese economy, it was found to be in accordance with the research results. |
format | Online Article Text |
id | pubmed-7021313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70213132020-02-26 Exponentially weighted moving average—Moving average charts for monitoring the process mean Sukparungsee, Saowanit Areepong, Yupaporn Taboran, Rattikarn PLoS One Research Article This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving Average—Moving Average Chart (EWMA-MA) to detect the mean change in a process underlying symmetric and asymmetric distributions. The performance of the proposed control chart are compared with Shewhart, MA, EWMA, MA-EWMA and EWMA-MA control charts by using average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) as the criteria for measuring efficiency which evaluated by using Monte Carlo simulation (MC), Moreover, the proposed control chart will be applied to real data. The results of performance comparison showed that the presented control charts performed better detection than the Shewhart, MA, and EWMA charts. However, the results of detection tended to be slower than those for the MA-EWMA chart. The value of ARL(1) for the mixed control chart depends on the parameters of the statistics for such control chart. The EWMA-MA chart is a variable following λ and the MA-EWMA chart is varied according to w. From applying the proposed control chart to the data for flow in the Nile River and data of the real GDP growth (%) in the Lebanese economy, it was found to be in accordance with the research results. Public Library of Science 2020-02-14 /pmc/articles/PMC7021313/ /pubmed/32059001 http://dx.doi.org/10.1371/journal.pone.0228208 Text en © 2020 Sukparungsee et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Sukparungsee, Saowanit Areepong, Yupaporn Taboran, Rattikarn Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title | Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title_full | Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title_fullStr | Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title_full_unstemmed | Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title_short | Exponentially weighted moving average—Moving average charts for monitoring the process mean |
title_sort | exponentially weighted moving average—moving average charts for monitoring the process mean |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7021313/ https://www.ncbi.nlm.nih.gov/pubmed/32059001 http://dx.doi.org/10.1371/journal.pone.0228208 |
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