MONITORING THE PROCESS VARIANCE USING GWMA FOR EXPONENTIALLY DISTRIBUTED CHARACTERISTICS

DOI10.17654/TS055020113OpenAlexW2944861919MaRDI QIDQ5036135

Ali Algarni

Publication date: 23 February 2022

Published in: Far East Journal of Theoretical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.17654/ts055020113

zbMATH Keywords

exponential distributionMonte Carlo simulationcontrol chartaverage run lengthgenerally weighted moving average statisticthe variance of the process

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30)

Cites Work

• Unnamed Item
• Using a new VSI EWMA average loss control chart to monitor changes in the difference between the process mean and target and/or the process variability
• Using one EWMA chart to jointly monitor the process mean and variance
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• Monitoring Process Mean and Variability with One Double EWMA Chart
• Generally weighted moving average control charts with fast initial response features
• MONITORING AUTOCORRELATED PROCESS MEAN AND VARIANCE USING A GWMA CHART BASED ON RESIDUALS
• Robustness to non-normality and autocorrelation of individuals control charts
• Monitoring process mean using generally weighted moving average chart for exponentially distributed characteristics
• A rational sequential probability ratio test control chart for monitoring process shifts in mean and variance
• Number of Replications Required in Control Chart Monte Carlo Simulation Studies
• Estimation of the Change Point in Monitoring the Process Mean and Variance

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