Homogeneously Weighted Moving Average Control Charts: Overview, Controversies, and New Directions

Jean-Claude Malela-Majika (), Schalk William Human and Kashinath Chatterjee
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Jean-Claude Malela-Majika: Department of Statistics, Faculty of Natural and Agricultural Sciences, University of Pretoria, Hatfield, Pretoria 0028, South Africa
Schalk William Human: Department of Statistics, Faculty of Natural and Agricultural Sciences, University of Pretoria, Hatfield, Pretoria 0028, South Africa
Kashinath Chatterjee: Department of Biostatistics and Data Science, Augusta University, Augusta, GA 30912, USA

Mathematics, 2024, vol. 12, issue 5, 1-30

Abstract: The homogeneously weighted moving average (HWMA) chart is a recent control chart that has attracted the attention of many researchers in statistical process control (SPC). The HWMA statistic assigns a higher weight to the most recent sample, and the rest is divided equally between the previous samples. This weight structure makes the HWMA chart more sensitive to small shifts in the process parameters when running in zero-state mode. Many scholars have reported its superiority over the existing charts when the process runs in zero-state mode. However, several authors have criticized the HWMA chart by pointing out its poor performance in steady-state mode due to its weighting structure, which does not reportedly comply with the SPC standards. This paper reviews and discusses all research works on HWMA-related charts (i.e., 55 publications) and provides future research ideas and new directions.

Keywords: homogeneously weighted moving average; double HWMA; conditional expected delay; HWMA; memory-type chart; Monte Carlo simulation; steady-state mode; triple HWMA; weight structure; zero-state mode (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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