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. 2022 Apr 22;50(10):2079-2107.
doi: 10.1080/02664763.2022.2064977. eCollection 2023.

A double generally weighted moving average control chart for monitoring the process variability

Vasileios Alevizakos  1 , Kashinath Chatterjee  2 , Christos Koukouvinos  1 , Angeliki Lappa  1
Affiliations

A double generally weighted moving average control chart for monitoring the process variability

Vasileios Alevizakos et al. J Appl Stat. .

Abstract

In the present article, a double generally weighted moving average (DGWMA) control chart based on a three-parameter logarithmic transformation is proposed for monitoring the process variability, namely the S2-DGWMA chart. Monte-Carlo simulations are utilized in order to evaluate the run-length performance of the S2-DGWMA chart. In addition, a detailed comparative study is conducted to compare the performance of the S2-DGWMA chart with several well-known memory-type control charts in the literature. The comparisons indicate that the proposed one is more efficient in detecting small shifts, while it is more sensitive in identifying upward shifts in the process variability. A real data example is given to present the implementation of the new S2-DGWMA chart.

Keywords: Average run-length; control chart; double generally weighted moving average; logarithmic transformation; process variability.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
The S2-EWMA control chart for the cylinder diameter data.
Figure 2.
Figure 2.
The S2-HEWMA control chart for the cylinder diameter data.
Figure 3.
Figure 3.
The S2-TEWMA control chart for the cylinder diameter data.
Figure 4.
Figure 4.
The S2-GWMA control chart for the cylinder diameter data.
Figure 5.
Figure 5.
The S2-DGWMA control chart for the cylinder diameter data.
See this image and copyright information in PMC

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