Integral-Equation Approach with Analytical Closed-Form ARL for DMEWMA Chart in ARMA Process: Enhancing Process-Change Detection

This research establishes a definitive closed-form equation for the average run length (ARL) of the double modified exponentially weighted moving average (DMEWMA) control chart employed for the ARMA(p,q) process. The proposed formula is derived analytically and validated through comparison with the numerical integral-equation (NIE) method. To assess the agreement between the two methods, we examine the percentage of accuracy. To evaluate the monitoring capabilities of the DMEWMA chart, additional performance metrics—SDRL and MRL—are computed across various chart design configurations. We use RMI, AEQL, and PCI to examine how well the DMEWMA chart detects mean-process shifts when applied to the modified EWMA (MEWMA) and the EWMA charts. A real-world example of monthly unemployment-rate production-index data from Bangkok and southern Thailand demonstrates the effectiveness of the explicit ARL-based DMEWMA chart in detecting changes in process means. The findings demonstrate that the DMEWMA chart outperforms the MEWMA and EWMA charts in identifying process shifts.

Authors

Institutions

Publication Details

Journal
WSEAS TRANSACTIONS on SYSTEMS archive
Published
2026-10-26
DOI
https://doi.org/10.37394/23202.2026.25.56
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integral-Equation Approach with Analytical Closed-Form ARL for DMEWMA Chart in ARMA Process: Enhancing Process-Change Detection

Saowanit Sukparungsee, Yupaporn Areepong
WSEAS TRANSACTIONS on SYSTEMS archive
Advanced Statistical Process Monitoring
article

Integral-Equation Approach with Analytical Closed-Form ARL for DMEWMA Chart in ARMA Process: Enhancing Process-Change Detection

Saowanit Sukparungsee, Yupaporn Areepong
article en

Abstract

This research establishes a definitive closed-form equation for the average run length (ARL) of the double modified exponentially weighted moving average (DMEWMA) control chart employed for the ARMA(p,q) process. The proposed formula is derived analytically and validated through comparison with the numerical integral-equation (NIE) method. To assess the agreement between the two methods, we examine the percentage of accuracy. To evaluate the monitoring capabilities of the DMEWMA chart, additional performance metrics—SDRL and MRL—are computed across various chart design configurations. We use RMI, AEQL, and PCI to examine how well the DMEWMA chart detects mean-process shifts when applied to the modified EWMA (MEWMA) and the EWMA charts. A real-world example of monthly unemployment-rate production-index data from Bangkok and southern Thailand demonstrates the effectiveness of the explicit ARL-based DMEWMA chart in detecting changes in process means. The findings demonstrate that the DMEWMA chart outperforms the MEWMA and EWMA charts in identifying process shifts.

WSEAS TRANSACTIONS on SYSTEMS archiveVol. 25
King Mongkut's University of Technology North Bangkok (TH)
King Mongkut's University of Technology North Bangkok
Openalex Percentile: Top 11%
Advanced Statistical Process Monitoring
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon