Variable sample size based EWMA control chart with an exponential scaling mechanism for production process monitoring

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Dades bibliogràfiques
Publicat a:	Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 30964-30974
Autor principal:	Nafisah, Ibrahim A.
Altres autors:	Almazah, Mohammed M. A., Al-Rezami, A. Y., Hussain, Saddam
Publicat:	Nature Publishing Group
Matèries:	Sample size Design Process control Performance assessment Statistical process control Normal distribution Monte Carlo simulation Control charts
Accés en línia:	Citation/Abstract Full Text Full Text - PDF
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Descripció
Resum:	Statistical Process Control is essential for ensuring process stability and detecting variations in a production environment. This study introduces a control chart based on the Exponentially Weighted Moving Average (EWMA) that uses an adaptive sample size. The proposed approach enhances shift detection by dynamically adjusting the sample size in response to changes in process variation. Extensive Monte Carlo simulations were performed to assess the performance of the proposed control chart, focusing on metrics such as the Average Run Length (ARL) and the Standard Deviation of Run Length (SDRL). The findings show that the new chart surpasses both the Fixed Sample Size EWMA (FEWMA) and the Variable Sample Size EWMA charts, particularly in detecting small to moderate shifts in the process. This approach strikes a balance between detection sensitivity and computational efficiency, enabling prompt identification of process changes while maintaining robustness during in-control conditions. To illustrate its practical applicability, a real-world dataset was analyzed, demonstrating the effectiveness of the proposed method in actual process monitoring scenarios.
ISSN:	2045-2322
DOI:	10.1038/s41598-025-16531-2
Font:	Science Database