Saghir, AamirKhan, Zahid YounasMalela-Majika, Jean ClaudeKosztyán, Zsolt Tibor2025-10-022025-10-022025-12Saghir, 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.2025.107278.2590-1230 (online)10.1016/j.rineng.2025.107278http://hdl.handle.net/2263/104576COMPUTATIONAL 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).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 implementationen© 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Control chartsStatistical process control (SPC)Risk-based control charts (RBCCs)AutocorrelationDecision errorExponentially weighted moving average (EWMA)Measurement uncertaintyOptimizationPhase IArticle