Scientific Reports (Mar 2024)

Nonparametric mixed exponentially weighted moving average-moving average control chart

  • Muhammad Ali Raza,
  • Azka Amin,
  • Muhammad Aslam,
  • Tahir Nawaz,
  • Muhammad Irfan,
  • Farah Tariq

DOI
https://doi.org/10.1038/s41598-024-57407-1
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 16

Abstract

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Abstract This research designed a distribution-free mixed exponentially weighted moving average-moving average (EWMA-MA) control chart based on signed-rank statistic to effectively identify changes in the process location. The EWMA-MA charting statistic assigns more weight to information obtained from the recent $$w$$ w samples and exponentially decreasing weights to information accumulated from all other past samples. The run-length profile of the proposed chart is obtained by employing Monte Carlo simulation techniques. The effectiveness of the proposed chart is evaluated under symmetrical distributions using a variety of individual and overall performance measures. The analysis of the run-length profile indicates that the proposed chart performs better than the existing control charts discussed in the literature. Additionally, an application from a gas turbine is provided to demonstrate how the proposed chart can be used in practice.

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