Monitoring a BAR(1) Process with EWMA and DEWMA Control Charts

Maria Anastasopoulou () and Athanasios C. Rakitzis ()
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Maria Anastasopoulou: University of the Aegean
Athanasios C. Rakitzis: University of the Aegean

A chapter in Control Charts and Machine Learning for Anomaly Detection in Manufacturing, 2022, pp 77-103 from Springer

Abstract: Abstract In this work we study one-sided and two-sided EWMA and Double EWMA control charts for monitoring an integer-valued autocorrelated process with a bounded support. The performance of the proposed charts is studied via simulation. We compare the performance of the proposed charts and provide aspects for the statistical design and practical implementation. The results of an extensive numerical study, that consists of the examination of a wide variety of out-of-control situations, show that none of the chart outperforms the other uniformly. Specifically, both charts have a difficulty in detecting decreasing shifts in the autocorrelation parameter. An illustrative example based on real data is also provided.

Keywords: Attributes control charts; Binomail AR(1); Integer-valued time series; Statistical process monitoring (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-030-83819-5_4

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DOI: 10.1007/978-3-030-83819-5_4

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