References
- Anwar, S. M., Aslam, M., Zaman, B., & Riaz, M. (2021). Mixed memory control chart based on auxiliary information for simultaneously monitoring of process parameters: An application in glass field Computers &. Computers & Industrial Engineering, 156, 107284. https://doi.org/10.1016/j.cie.2021.107284
- Chen, G., Cheng, S. W., & Xie, H. (2001). Monitoring process mean and variability with one EWMA chart. Journal of Quality Technology, 33(2), 223–233. https://doi.org/10.1080/00224065.2001.11980069
- Cheng, S. W., & Thaga, K. (2010). The Max-CUSUM chart. In H.-J. Lenz, P.-T. Wilrich, & W. Schmid (Eds.), Frontiers in Statistical Quality Control 9, chapter 6 (pp. 85–98). Springer.
- Crosier, R. B. (1986). A new two-sided cumulative sum quality control scheme. Technometrics, 28(3), 187–194. https://doi.org/10.1080/00401706.1986.10488126
- Haq, A. (2017). A new maximum EWMA control chart for simultaneously monitoring process mean and dispersion using auxiliary information. Quality and Reliability Engineering International, 33(7), 1577–1587. https://doi.org/10.1002/qre.2126
- Haq, A. (2020). A maximum adaptive exponentially weighted moving average control chart for monitoring process mean and variability. Quality Technology & Quantitative Management, 17(1), 16–31. https://doi.org/10.1080/16843703.2018.1530181
- Haq, A., & Akhtar, S. (2020). Auxiliary information based maximum EWMA and DEWMA charts with variable sampling intervals for process mean and variance. Communications in Statistics - Theory and Methods, 0(0), 1–22.
- Haq, A., & Bibi, L. (2019). A new dual CUSUM mean chart. Quality and Reliability Engineering International, 35(4), 1245–1262. https://doi.org/10.1002/qre.2457
- Haq, A., Brown, J., & Moltchanova, E. (2015). A new maximum exponentially weighted moving average control chart for monitoring process mean and dispersion. Quality and Reliability Engineering International, 31(8), 1587–1610. https://doi.org/10.1002/qre.1694
- Haq, A., & Razzaq, F. (2020). Maximum weighted adaptive CUSUM charts for simultaneous monitoring of process mean and variance. Journal of Statistical Computation and Simulation, 90(16), 2949–2974. https://doi.org/10.1080/00949655.2020.1793154
- Jalilibal, Z., Amiri, A., & Khoo, M. B. C. (2022). A literature review on joint control schemes in statistical process monitoring. Quality and Reliability Engineering International, 38(6), 3270–3289. https://doi.org/10.1002/qre.3114
- Khoo, M. B. C., Teh, S. Y., & Wu, Z. (2010). Monitoring process mean and variability with one double EWMA chart. Communications in Statistics - Theory and Methods, 39(20), 3678–3694. https://doi.org/10.1080/03610920903324866
- Lee, P. -H. (2013). Joint statistical design of X ¯and s charts with combined double sampling and variable sampling interval. European Journal of Operational Research, 225(2), 285–297. https://doi.org/10.1016/j.ejor.2012.08.020
- Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley.
- Sheu, S. -H., Huang, C. -J., & Hsu, T. -S. (2012). Extended maximum generally weighted moving average control chart for monitoring process mean and variability. Computers & Industrial Engineering, 62(1), 216–225. https://doi.org/10.1016/j.cie.2011.09.009
- Wu, Z., & Tian, Y. (2005). Weighted-loss-function CUSUM chart for monitoring mean and variance of a production process. International Journal of Production Research, 43(14), 3027–3044. https://doi.org/10.1080/00207540500057639
- Xie, H. (1999). Contributions to qualimentry. PhD thesis, Department of Statistics, The University of Manitoba,
- Zhao, Y., Tsung, F., & Wang, Z. (2005). Dual CUSUM control schemes for detecting a range of mean shifts. IIE Transactions, 37(11), 1047–1057. https://doi.org/10.1080/07408170500232321