Max-mixed EWMA control chart for joint monitoring of mean and variance: an application to yogurt packing process

The Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and moderate shifts in the mean and variance of a process by com...

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Bibliographic Details
Published in:Scientific reports 2024-05, Vol.14 (1), p.10372-10372, Article 10372
Main Authors: Malik, Seher, Hanif, Muhammad, Noor-ul-Amin, Muhammad, Khan, Imad, Ahmad, Bakhtiyar, Abaker, Abdelgalal O. I., Ahmed Darwish, Jumanah
Format: Article
Language:English
Subjects:
639/705/1041
639/705/1045
639/705/1046
639/705/531
Control charts
Defective products
EWMA
Humanities and Social Sciences
Joint monitoring control chart
Max mixed EWMA statistics
Max-EWMA control chart
multidisciplinary
Normal distribution
Process control
Process controls
Quality control
Science
Science (multidisciplinary)
Statistical analysis
Statistical process control
Statistics
Yogurt
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Summary:The Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and moderate shifts in the mean and variance of a process by comparing the maximum of two statistics, one based on the mean and the other on the variance. In this paper, we propose a new MM EWMA control chart. The proposed chart is compared with existing control charts using simulation studies, and the results show that the chart performs better in detecting small and moderate shifts in both the mean and variance. The proposed chart can be helpful in quality control applications, where joint monitoring of mean and variance is necessary to ensure a product’s or process’s quality. The real-life application of the proposed control chart on yogurt packing in a cup data set shows the outperformance of the MM EWMA control chart. Both simulations & real-life application results demonstrate the better performance of the proposed chart in detecting smaller shifts during the production process.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-61132-0