Adaptive EWMA-S² control charts with adaptive smoothing parameter

References

• Acosta-Mejia, C. A., J. J. Pignatiello, and B. V. Rao. 1999. A comparison of control charting procedures for monitoring process dispersion. IIE Transactions 31 (6):569–79. doi:10.1080/07408179908969859.
   Web of Science ®Google Scholar
• Bagshaw, M., and R. A. Johnson. 1975. The effect of serial correlation on the performance of CUSUM tests II. Technometrics 17 (1):73–80. doi:10.1080/00401706.1975.10489274.
   Web of Science ®Google Scholar
• Box, G. E., W. G. Hunter, and J. S. Hunter. 1978. Statistics for experimenters. New York: John Wiley & Sons.
   Google Scholar
• Brook, D., and D. A. Evans. 1972. An approach to the probability distribution of CUSUM run length. Biometrika 59 (3):539–49. doi:10.1093/biomet/59.3.539.
   Web of Science ®Google Scholar
• Capizzi, G., and G. Masarotto. 2003. An adaptive exponentially weighted moving average control chart. Technometrics 45 (3):199–207. doi:10.1198/004017003000000023.
   Web of Science ®Google Scholar
• Castagliola, P. 2005. A new S2-EWMA control chart for monitoring the process variance. Quality and Reliability Engineering International 21 (8):781–94. doi:10.1002/qre.686.
   Web of Science ®Google Scholar
• Castagliola, P., G. Celano, and S. Fichera. 2009. A new CUSUM-S2 control chart for monitoring the process variance. Journal of Quality in Maintenance Engineering 15 (4):344–57. doi:10.1108/13552510910997724.
   Google Scholar
• Castagliola, P., G. Celano, and S. Fichera. 2010. A Johnson’s type transformation EWMA-S2 control chart. International Journal of Quality Engineering and Technology 1 (3):253–75. doi:10.1504/IJQET.2010.034611.
   Google Scholar
• Chang, T. C., and F. F. Gan. 1995. Cumulative sum control chart for monitoring process variance. Journal of Quality Technology 27 (2):109–19. doi:10.1080/00224065.1995.11979574.
   Web of Science ®Google Scholar
• Crowder, S. V., and M. D. Hamilton. 1992. An EWMA for monitoring a process standard deviation. Journal of Quality Technology 24 (1):12–21. doi:10.1080/00224065.1992.11979369.
   Web of Science ®Google Scholar
• Haq, A., J. Brown, and E. Moltchanova. 2015. New exponentially weighted moving average control charts for monitoring process mean and process dispersion. Quality and Reliability Engineering International 31 (5):877–901. doi:10.1002/qre.1646.
   Web of Science ®Google Scholar
• Hawkins, D. M. 1981. A CUSUM for a scale parameter. Journal of Quality Technology 13 (4):228–31. doi:10.1080/00224065.1981.11978762.
   Web of Science ®Google Scholar
• Huwang, L., C. J. Huang, and Y. H. T. Wang. 2010. New EWMA control charts for monitoring process dispersion. Computational Statistics & Data Analysis 54 (10):2328–42. doi:10.1016/j.csda.2010.03.011.
   Web of Science ®Google Scholar
• Johnson, N. L. 1949. Systems of frequency curves generated by methods of translation. Biometrika 36 (Pt. 1-2):149–76. doi:10.1093/biomet/36.1-2.149.
   PubMed Web of Science ®Google Scholar
• Johnson, N. L., S. Kotz, and N. Balakrishnan. 1994. Continuous univariate distributions. New York: Wiley.
   Google Scholar
• Li, Z., Y. Luo, and Z. Wang. 2010. Cusum of q chart with variable sampling intervals for monitoring the process mean. International Journal of Production Research 48 (16):4861–76. doi:10.1080/00207540903074983.
   Web of Science ®Google Scholar
• Li, Z., and Z. Wang. 2010. Adaptive cusum of the q chart. International Journal of Production Research 48 (5):1287–301. doi:10.1080/00207540802484937.
   Web of Science ®Google Scholar
• Li, Z., J. Zhang, and Z. Wang. 2010. Self-starting control chart for simultaneously monitoring process mean and variance. International Journal of Production Research 48 (15):4537–53. doi:10.1080/00207540903051692.
   Web of Science ®Google Scholar
• Li, Z., C. Zou, Z. Gong, and Z. Wang. 2014. The computation of average run length and average time to signal: An overview. Journal of Statistical Computation and Simulation 84 (8):1779–802. doi:10.1080/00949655.2013.766737.
   Web of Science ®Google Scholar
• Lowry, C. A., C. W. Champ, and W. H. Woodall. 1995. The performance of control charts for monitoring process variation. Communications in Statistics - Simulation and Computation 24 (2):409–37. doi:10.1080/03610919508813250.
   Web of Science ®Google Scholar
• Lucas, J. M., and M. S. Saccucci. 1990. Exponentially weighted moving average control schemes: Properties and Enhancements (with discussion). Technometrics 32 (1):1–29. doi:10.1080/00401706.1990.10484583.
   Web of Science ®Google Scholar
• Nazir, H. Z., M. Riaz, and R. J. Does. 2015. Robust CUSUM control charting for process dispersion. Quality and Reliability Engineering International 31 (3):369–79. doi:10.1002/qre.1596.
   Web of Science ®Google Scholar
• Page, E. S. 1963. Controlling the standard deviation by CUSUMS and warning lines. Technometrics 5 (3):307–15. doi:10.1080/00401706.1963.10490100.
   Web of Science ®Google Scholar
• Psarakis, S. 2015. Adaptive control charts: Recent developments and extensions. Quality and Reliability Engineering International 31 (7):1265–80. doi:10.1002/qre.1850.
   Web of Science ®Google Scholar
• Sánchez, I. 2006. Recursive estimation of dynamic models using Cook’s distance, with application to wind energy forecast. Technometrics 48 (1):61–73. doi:10.1198/004017005000000364.
   Web of Science ®Google Scholar
• Shewhart, W. A. 1931. Economic control of quality of manufactured product. New York: Van Nostrand.
   Google Scholar
• Shu, L. 2008. An adaptive exponentially weighted moving average control chart for monitoring process variances. Journal of Statistical Computation and Simulation 78 (4):367–84. doi:10.1080/00949650601108000.
   Web of Science ®Google Scholar
• Shu, L., and W. Jiang. 2008. A new EWMA chart for monitoring process dispersion. Journal of Quality Technology 40 (3):319–31. doi:10.1080/00224065.2008.11917737.
   Web of Science ®Google Scholar
• Shu, L., H. F. Yeung, and W. Jiang. 2010. An adaptive CUSUM procedure for signaling process variance changes of unknown sizes. Journal of Quality Technology 42 (1):69–85. doi:10.1080/00224065.2010.11917807.
   Web of Science ®Google Scholar
• Sparks, R. S. 2000. CUSUM charts for signaling varying location shifts. Journal of Quality Technology 32 (2):157–71. doi:10.1080/00224065.2000.11979987.
   Web of Science ®Google Scholar
• Ugaz, W., I. Sánchez, and A. M. Alonso. 2017. Adaptive EWMA control charts with time-varying smoothing parameter. The International Journal of Advanced Manufacturing Technology 93 (9–12):3847–58. doi:10.1007/s00170-017-0792-1.
   Web of Science ®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