Optimal design of risk-based average charts for autocorrelated measurements
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Date
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Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Please read abstract in the article.
HIGHLIGHTS
• Developed two Risk-Based (RB) average charts for monitoring autoregressive processes
• Design improves RB chart cost-efficiency under autocorrelated conditions
• TCharts validated via real-world data and autocorrelated simulations
• Sensitivity analysis conducted to support practical implementation
Description
COMPUTATIONAL CODE AVAILABILITY : The R code used in this study is available from the corresponding author upon request and is ready for direct application by practitioners and researchers.
DATA AVAILABILITY : Data sharing does not apply to this article, as no new data were created or analyzed in this study. The real dataset is publicly available in the rbcc R package under the name t2uc (https://CRAN.R-project.org/package=rbcc).
Keywords
Control charts, Statistical process control (SPC), Risk-based control charts (RBCCs), Autocorrelation, Decision error, Exponentially weighted moving average (EWMA), Measurement uncertainty, Optimization, Phase I
Sustainable Development Goals
SDG-12: Responsible consumption and production
Citation
Saghir, A., Khan, Z.Y., Malela-Majika, J.C. & Kosztyán, Z.T. 2025, 'Optimal design of risk-based average charts for autocorrelated measurements', Results in Engineering, vol. 28, art. 107278, pp. 1-13, doi : 10.1016/j.rineng.2025.107278.