LAPSE:2023.2187
Published Article

LAPSE:2023.2187
On Reassessment of the HWMA Chart for Process Monitoring
February 21, 2023
Abstract
In the recent literature of process monitoring, homogeneously weighted moving average (HWMA) type control charts have become quite popular. These charts are quite efficient for early detection of shifts, especially of smaller magnitudes, in process parameters such as location and dispersion. A recent study pointed out a few concerns related to HWMA charts that mainly relate to its steady-state performance. It needs to be highlighted that the initial studies on HWMA focused only on the zero-state performance of the chart relative to other well-known memory charts. This study reinvestigates the performance of the HWMA chart under zero and steady states at various shifts. Using the Monte Carlo simulation method, a detailed comparative analysis of the HWMA chart is carried out relative to the exponentially weighted moving average (EWMA) chart with time-varying limits. For several values of design parameters, the in-control and out-of-control performance of these charts is evaluated in terms of the average run length (ARL). It has been observed that the structure of the HWMA chart has the ability to safeguard the detection ability and the run-length properties under various delays in process shifts. More specifically, it has been found that HWMA chart is superior to the EWMA chart for several shift sizes under zero state and is capable of maintaining its dominance in case the process experiences a delay in shift. However, the steady-state performance depends on the suitable choice of design parameters. This study provides clear cut-offs where HWMA and EWMA are superior to one another in terms of efficient monitoring of the process parameters.
In the recent literature of process monitoring, homogeneously weighted moving average (HWMA) type control charts have become quite popular. These charts are quite efficient for early detection of shifts, especially of smaller magnitudes, in process parameters such as location and dispersion. A recent study pointed out a few concerns related to HWMA charts that mainly relate to its steady-state performance. It needs to be highlighted that the initial studies on HWMA focused only on the zero-state performance of the chart relative to other well-known memory charts. This study reinvestigates the performance of the HWMA chart under zero and steady states at various shifts. Using the Monte Carlo simulation method, a detailed comparative analysis of the HWMA chart is carried out relative to the exponentially weighted moving average (EWMA) chart with time-varying limits. For several values of design parameters, the in-control and out-of-control performance of these charts is evaluated in terms of the average run length (ARL). It has been observed that the structure of the HWMA chart has the ability to safeguard the detection ability and the run-length properties under various delays in process shifts. More specifically, it has been found that HWMA chart is superior to the EWMA chart for several shift sizes under zero state and is capable of maintaining its dominance in case the process experiences a delay in shift. However, the steady-state performance depends on the suitable choice of design parameters. This study provides clear cut-offs where HWMA and EWMA are superior to one another in terms of efficient monitoring of the process parameters.
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Keywords
exponentially weighted moving average chart, homogeneously weighted moving average chart, steady state, zero state
Subject
Suggested Citation
Riaz M, Ahmad S, Mahmood T, Abbas N. On Reassessment of the HWMA Chart for Process Monitoring. (2023). LAPSE:2023.2187
Author Affiliations
Riaz M: Department of Mathematics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia [ORCID]
Ahmad S: Department of Mathematics, COMSATS University Islamabad, Wah Cantt Campus, Punjab 47040, Pakistan
Mahmood T: Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia; Interdisciplinary Research Centre for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran 31261, [ORCID]
Abbas N: Department of Mathematics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia [ORCID]
Ahmad S: Department of Mathematics, COMSATS University Islamabad, Wah Cantt Campus, Punjab 47040, Pakistan
Mahmood T: Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia; Interdisciplinary Research Centre for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran 31261, [ORCID]
Abbas N: Department of Mathematics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia [ORCID]
Journal Name
Processes
Volume
10
Issue
6
First Page
1129
Year
2022
Publication Date
2022-06-05
ISSN
2227-9717
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Original Submission
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PII: pr10061129, Publication Type: Journal Article
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LAPSE:2023.2187
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https://doi.org/10.3390/pr10061129
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