A Multivariate Homogeneously Weighted Moving Average Control Chart

This paper presents a multivariate homogeneously weighted moving average (MHWMA) control chart for monitoring a process mean vector. The MHWMA control chart statistic gives a specific weight to the current observation, and the remaining weight is evenly distributed among the previous observations. W...

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Bibliographic Details
Published inIEEE access Vol. 7; pp. 9586 - 9597
Main Authors Adegoke, Nurudeen A., Abbasi, Saddam Akber, Smith, Adam N. H., Anderson, Marti J., Pawley, Matthew D. M.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Average run length
control chart
Control charts
Covariance matrices
manufacturing process
Monitoring
Multivariate analysis
Process control
quality control
Sensitivity
Smoothing methods
statistical process control
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Summary:This paper presents a multivariate homogeneously weighted moving average (MHWMA) control chart for monitoring a process mean vector. The MHWMA control chart statistic gives a specific weight to the current observation, and the remaining weight is evenly distributed among the previous observations. We present the design procedure and compare the average run length (ARL) performance of the proposed chart with multivariate Chi-square, multivariate EWMA, and multivariate cumulative sum control charts. The ARL comparison indicates superior performance of the MHWMA chart over its competitors, particularly for the detection of small shifts in the process mean vector. Examples are also provided to show the application of the proposed chart.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2891988