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Development of a VSS-EWMA chart for coefficient of variation with application to production process
by
Nabi, Muhammad
, Safeer, Amna
, Elwahab, Maysaa Elmahi Abd
in
639/166
/ 639/705
/ Average run length
/ Coefficient of variation
/ Comparative analysis
/ Control charts
/ Electronics industry
/ EWMA control chart
/ Humanities and Social Sciences
/ multidisciplinary
/ Normal distribution
/ Process controls
/ Process variability monitoring
/ Random variables
/ Sample size
/ Science
/ Science (multidisciplinary)
/ SPC
/ VSS
2025
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Development of a VSS-EWMA chart for coefficient of variation with application to production process
by
Nabi, Muhammad
, Safeer, Amna
, Elwahab, Maysaa Elmahi Abd
in
639/166
/ 639/705
/ Average run length
/ Coefficient of variation
/ Comparative analysis
/ Control charts
/ Electronics industry
/ EWMA control chart
/ Humanities and Social Sciences
/ multidisciplinary
/ Normal distribution
/ Process controls
/ Process variability monitoring
/ Random variables
/ Sample size
/ Science
/ Science (multidisciplinary)
/ SPC
/ VSS
2025
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Do you wish to request the book?
Development of a VSS-EWMA chart for coefficient of variation with application to production process
by
Nabi, Muhammad
, Safeer, Amna
, Elwahab, Maysaa Elmahi Abd
in
639/166
/ 639/705
/ Average run length
/ Coefficient of variation
/ Comparative analysis
/ Control charts
/ Electronics industry
/ EWMA control chart
/ Humanities and Social Sciences
/ multidisciplinary
/ Normal distribution
/ Process controls
/ Process variability monitoring
/ Random variables
/ Sample size
/ Science
/ Science (multidisciplinary)
/ SPC
/ VSS
2025
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Development of a VSS-EWMA chart for coefficient of variation with application to production process
Journal Article
Development of a VSS-EWMA chart for coefficient of variation with application to production process
2025
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Overview
This study introduces a novel Variable Sample Size Exponentially Weighted Moving Average (VSS-EWMA) control chart for monitoring the coefficient of variation, termed as Dynamic Adaptive CV (DACV) chart. Tailored for dynamic production settings where both the process mean and variability are subject to change, the proposed chart integrates an adaptive sampling strategy within the EWMA framework, allowing real-time adjustment of sample size in response to process conditions. Comparative analysis with the conventional Fixed Sample Size EWMA (FEWMA) chart reveals that DACV chart exhibits enhanced sensitivity in detecting small to moderate shifts in variability. Its performance is rigorously evaluated using Average Run Length (ARL), Standard Deviation of Run Length (SDRL), and run-length percentiles. Visualizations through heat maps further affirm its robustness across a wide range of shift magnitudes and smoothing parameters. A real-world application using semiconductor manufacturing data demonstrates the practical utility of DACV chart, underscoring its potential in contemporary quality monitoring systems.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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