A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes

A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes

Generalized exponentially weighted moving average (EWMA) and double EWMA (DEWMA) charts based on the Conway–Maxwell–Poisson (CMP or COM-Poisson) distribution, also known as the GEWMA and CMP-DEWMA charts, are effectively used for monitoring the counts of non-conformities in a process. To further enh...

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Bibliographic Details
Main Author: Jen-Hsiang Chen
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Symmetry
Subjects:
attributes
average run lengths
COM-Poisson distribution
DEWMA chart
DGWMA chart
Online Access:https://www.mdpi.com/2073-8994/12/6/1014
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spelling doaj-dd093c94339b4b0bace692fb9e16f08e2020-11-25T03:48:48ZengMDPI AGSymmetry2073-89942020-06-01121014101410.3390/sym12061014A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson ProcessesJen-Hsiang Chen0Department of Information Management, Shih Chien University Kaohsiung Campus, 200 University Road, Neimen District, Kaohsiung City 84550, TaiwanGeneralized exponentially weighted moving average (EWMA) and double EWMA (DEWMA) charts based on the Conway–Maxwell–Poisson (CMP or COM-Poisson) distribution, also known as the GEWMA and CMP-DEWMA charts, are effectively used for monitoring the counts of non-conformities in a process. To further enhance their performance, this study utilizes design and adjustment parameters to develop generally weighted moving average (GWMA) and double GWMA charts, also known as the CMP-GWMA and CMP-DGWMA charts, to monitor COM-Poisson attributes. Numerical simulations indicate that the CMP-DGWMA chart outperforms its prototype CMP-DEWMA and CMP-GWMA charts in detecting small location and dispersion shifts, as well as both shifts together, in terms of average run lengths. Finally, an example is provided to demonstrate the efficiency of the proposed CMP-DGWMA chart and its counterparts.https://www.mdpi.com/2073-8994/12/6/1014attributesaverage run lengthsCOM-Poisson distributionDEWMA chartDGWMA chart
collection DOAJ
language English
format Article
sources DOAJ
author Jen-Hsiang Chen
spellingShingle Jen-Hsiang Chen
A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
Symmetry
attributes
average run lengths
COM-Poisson distribution
DEWMA chart
DGWMA chart
author_facet Jen-Hsiang Chen
author_sort Jen-Hsiang Chen
title A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
title_short A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
title_full A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
title_fullStr A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
title_full_unstemmed A Double Generally Weighted Moving Average Chart for Monitoring the COM-Poisson Processes
title_sort double generally weighted moving average chart for monitoring the com-poisson processes
publisher MDPI AG
series Symmetry
issn 2073-8994
publishDate 2020-06-01
description Generalized exponentially weighted moving average (EWMA) and double EWMA (DEWMA) charts based on the Conway–Maxwell–Poisson (CMP or COM-Poisson) distribution, also known as the GEWMA and CMP-DEWMA charts, are effectively used for monitoring the counts of non-conformities in a process. To further enhance their performance, this study utilizes design and adjustment parameters to develop generally weighted moving average (GWMA) and double GWMA charts, also known as the CMP-GWMA and CMP-DGWMA charts, to monitor COM-Poisson attributes. Numerical simulations indicate that the CMP-DGWMA chart outperforms its prototype CMP-DEWMA and CMP-GWMA charts in detecting small location and dispersion shifts, as well as both shifts together, in terms of average run lengths. Finally, an example is provided to demonstrate the efficiency of the proposed CMP-DGWMA chart and its counterparts.
topic attributes
average run lengths
COM-Poisson distribution
DEWMA chart
DGWMA chart
url https://www.mdpi.com/2073-8994/12/6/1014
work_keys_str_mv AT jenhsiangchen adoublegenerallyweightedmovingaveragechartformonitoringthecompoissonprocesses
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