On efficient change point detection using a step cumulative sum control chart

References

• Abbas, N. 2015. Progressive mean as a special case of exponentially weighted moving average. Quality and Reliability Engineering International 31 (4):719–20. doi:10.1002/qre.1613.
   Web of Science ®Google Scholar
• Abbas, N., and M. Riaz. 2022. Progressive mean as a special case of exponentially weighted moving average: Discussion. Quality and Reliability Engineering International 38 (4):2188–97. doi:10.1002/qre.3056.
   Web of Science ®Google Scholar
• Abbas, N., M. Riaz, and R. J. M. M. Does. 2013. Mixed exponentially weighted moving average–cumulative sum charts for process monitoring. Quality and Reliability Engineering International 29 (3):345–56. doi:10.1002/qre.1385.
   Web of Science ®Google Scholar
• Abbas, N., R. F. Zafar, M. Riaz, and Z. Hussain. 2013. Progressive mean control chart for monitoring process location parameter. Quality and Reliability Engineering International 29 (3):357–67. doi:10.1002/qre.1386.
   Web of Science ®Google Scholar
• Ahmad, S., M. Riaz, S. A. Abbasi, and Z. Lin. 2013. On monitoring process variability under double sampling scheme. International Journal of Production Economics 142 (2):388–400. doi:10.1016/j.ijpe.2012.12.015.
   Web of Science ®Google Scholar
• Ahmad, S., M. Riaz, S. A. Abbasi, and Z. Lin. 2014. On efficient median control charting. Journal of the Chinese Institute of Engineers 37 (3):358–75. doi:10.1080/02533839.2013.781794.
   Web of Science ®Google Scholar
• Alevizakos, V., K. Chatterjee, C. Koukouvinos, and A. Lappa. 2022. A double generally weighted moving average control chart for monitoring the process variability. Journal of Applied Statistics 1–29. doi:10.1080/02664763.2022.2064977.
   PubMed Web of Science ®Google Scholar
• Awais, M., and A. Haq. 2018. An EWMA chart for monitoring process mean. Journal of Statistical Computation and Simulation 88 (5):1003–25. doi:10.1080/00949655.2017.1421193.
   Web of Science ®Google Scholar
• Crowder, S. V. 1989. Design of exponentially weighted moving average schemes. Journal of Quality Technology 21 (3):155–62. doi:10.1080/00224065.1989.11979164.
   Web of Science ®Google Scholar
• Fu, M. C., and J.-Q. Hu. 1999. Efficient design and sensitivity analysis of control charts using monte carlo simulation. Management Science 45 (3):395–413. doi:10.1287/mnsc.45.3.395.
   Web of Science ®Google Scholar
• Haq, A., and W. Munir. 2018. Improved CUSUM charts for monitoring process mean. Journal of Statistical Computation and Simulation 88 (9):1684–701. doi:10.1080/00949655.2018.1444040.
   Web of Science ®Google Scholar
• Hawkins, D. M., and Q. Wu. 2014. The CUSUM and the EWMA head-to-head. Quality Engineering 26 (2):215–22. doi:10.1080/08982112.2013.817014.
   Web of Science ®Google Scholar
• Knoth, S., N. A. Saleh, M. A. Mahmoud, W. H. Woodall, and V. G. Tercero-Gómez. 2023. A critique of a variety of “memory-based” process monitoring methods. Journal of Quality Technology 55 (1):18–42. doi:10.1080/00224065.2022.2034487.
   Web of Science ®Google Scholar
• Lucas, J. M. 1982. Combined Shewhart-CUSUM quality control schemes. Journal of Quality Technology 14 (2):51–9. doi:10.1080/00224065.1982.11978790.
   Web of Science ®Google Scholar
• Mehmood, R., M. Riaz, and R. J. M. M. Does. 2013. Efficient power computation for r out of m runs rules schemes. Computational Statistics 28 (2):667–81. doi:10.1007/s00180-012-0322-4.
   Web of Science ®Google Scholar
• Montgomery, D. C. 2019. Introduction to statistical quality control, 8th ed. Hoboken, NJ: Wiley.
   Google Scholar
• Nazir, H. Z., M. Riaz, R. J. Does, and N. Abbas. 2013. Robust CUSUM control charting. Quality Engineering 25 (3):211–24. doi:10.1080/08982112.2013.769057.
   Web of Science ®Google Scholar
• Ou, Y., Z. Wu, and T. N. Goh. 2011. A new SPRT chart for monitoring process mean and variance. International Journal of Production Economics 132 (2):303–14. doi:10.1016/j.ijpe.2011.05.002.
   Web of Science ®Google Scholar
• Ou, Y., Z. Wu, and F. Tsung. 2012. A comparison study of effectiveness and robustness of control charts for monitoring process mean. International Journal of Production Economics 135 (1):479–90. doi:10.1016/j.ijpe.2011.08.026.
   Web of Science ®Google Scholar
• Page, E. S. 1954. Continuous inspection schemes. Biometrika 41 (1–2):100–15. doi:10.2307/2333009.
   Web of Science ®Google Scholar
• Riaz, M., M. Abid, Z. Abbas, and H. Z. Nazir. 2021. An enhanced approach for the progressive mean control charts: A discussion and comparative analysis. Quality and Reliability Engineering International 37 (1):1–9. doi:10.1002/qre.2733.
   Web of Science ®Google Scholar
• Roberts, S. W. 1959. Control chart tests based on geometric moving averages. Technometrics 1 (3):239–50. doi:10.2307/1266443.
   Google Scholar
• Ryu, J.-H., G. Wan, and S. Kim. 2010. Optimal design of a CUSUM chart for a mean shift of unknown size. Journal of Quality Technology 42 (3):311–26. doi:10.1080/00224065.2010.11917826.
   Web of Science ®Google Scholar
• Shewhart, W. A. 1931. Economic control of quality of manufactured product. Oxford, England: Van Nostrand.
   Google Scholar
• Wu, Z., J. Jiao, M. Yang, Y. Liu, and Z. Wang. 2009. An enhanced adaptive CUSUM control chart. IIE Transactions 41 (7):642–53. doi:10.1080/07408170802712582.
   Web of Science ®Google Scholar
• Zhang, S., and Z. Wu. 2006. Monitoring the process mean and variance using a weighted loss function CUSUM scheme with variable sampling intervals. IIE Transactions 38 (4):377–87. doi:10.1080/07408170500232578.
   Web of Science ®Google Scholar