A New Maximum Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean and Dispersion

Abdul Haq · Jennifer Brown · Elena V. Moltchanova

28 citations0/0 files storedQuality and Reliability Engineering International

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Survey Sampling and Estimation Techniques

Abstract

Maximum exponentially weighted moving average (MaxEWMA) control charts have attracted substantial interest because of their ability to simultaneously detect increases and decreases in both the process mean and the process variability. In this paper, we propose new MaxEWMA control charts based on ordered double ranked set sampling (ODRSS) and ordered imperfect double ranked set sampling (OIDRSS) schemes, named MaxEWMA‐ODRSS and MaxEWMA‐OIDRSS control charts, respectively. The proposed MaxEWMA control charts are based on the best linear unbiased estimators obtained under ODRSS and OIDRSS schemes. Extensive Monte Carlo simulations are used to estimate the average run length and standard deviation of the run length of the proposed MaxEWMA control charts. The run length performances and the diagnostic abilities of the proposed MaxEWMA control charts are compared with that of their counterparts based on simple random sampling (SRS), ordered ranked set sampling (ORSS) and ordered imperfect ranked set sampling schemes (OIRSS) schemes, that is, MaxEWMA‐SRS, maximum generally weighted moving average (MaxGWMA‐SRS), MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts. It turns out that the proposed MaxEWMA‐ODRSS and MaxEWMA‐OIDRSS control charts perform uniformly better than the MaxEWMA‐SRS, MaxGWMA‐SRS, MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts in simultaneous detection of shifts in the process mean and variability. An application to real data is also provided to illustrate the implementations of the proposed and existing MaxEWMA control charts. Copyright © 2014 John Wiley & Sons, Ltd.

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References

1959Control Chart Tests Based on Geometric Moving Averages 1988Introduction to Statistical Quality Control 1992An EWMA for Monitoring a Process Standard Deviation 2001Monitoring Process Mean and Variability with One EWMA Chart 2012Mixed Exponentially Weighted Moving Average–Cumulative Sum Charts for Process Monitoring 2010Enhancing the performance of EWMA charts 1995On Properties ofQCharts for Variables 2012A New Hybrid Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean

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2018An EWMA chart for monitoring process mean 2016Monitoring simple linear profiles in multistage processes by a MaxEWMA control chart 2017Sign control chart based on ranked set sampling 2021An Efficient Robust Nonparametric Triple EWMA Wilcoxon Signed-Rank Control Chart for Process Location 2023A review of ranked set sampling and modified methods in designing control charts 2020Maximum weighted adaptive CUSUM charts for simultaneous monitoring of process mean and variance

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