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Articles

A generalized exponentially weighted moving average control chart for monitoring autocorrelated vectors

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Pages 2559-2577 | Received 20 Feb 2019, Accepted 24 Mar 2021, Published online: 06 Apr 2021

References

  • Alwan, L. C., and D. Radson. 1992. Time-series investigation of subsample mean charts. IIE Transactions 24 (5):66–80. doi:10.1080/07408179208964246.
  • Alwan, L. C., and H. V. Roberts. 1988. Time-series modeling for statistical process control. Journal of Business & Economic Statistics 6 (1):87–95. doi:10.2307/1391421.
  • Aparisi, F., and C. L. Haro. 2003. A comparison of T2 control charts with variable sampling schemes as opposed to MEWMA chart. International Journal of Production Research 41 (10):2169–82. doi:10.1080/0020754031000138655.
  • Brockwell, P. J., and R. A. Davis. 2016. Introduction to time series and forecasting. New York: Springer.
  • Epprecht, E. K., M. A. de Luna, and F. Aparisi. 2011. Joint EWMA charts for multivariate process control: Markov chain and optimal design. International Journal of Production Research 49 (23):7151–69. doi:10.1080/00207543.2010.537383.
  • Hawkins, D. M., S. Choi, and S. Lee. 2007. A general multivariate exponentially weighted moving-average control chart. Journal of Quality Technology 39 (2):118–25. doi:10.1080/00224065.2007.11917679.
  • Huang, X., S. Bisgaard, and N. Xu. 2014. Model-based multivariate monitoring charts for autocorrelated processes. Quality and Reliability Engineering International 30 (4):527–43. doi:10.1002/qre.1506.
  • Huh, I., R. Viveros-Aguilera, and N. Balakrishnan. 2013. Differential smoothing in the bivariate exponentially weighted moving average chart. Journal of Quality Technology 45 (4):377–93. doi:10.1080/00224065.2013.11917945.
  • Jensen, W. A., L. A. Jones-Farmer, C. W. Champ, and W. H. Woodall. 2006. Effects of parameter estimation on control chart properties: A literature review. Journal of Quality Technology 38 (4):349–64. doi:10.1080/00224065.2006.11918623.
  • Jiang, W., K.-L. Tsui, and W. H. Woodall. 2000. A new SPC monitoring method: The ARMA chart. Technometrics 42 (4):399–410. doi:10.1080/00401706.2000.10485713.
  • Johnson, R. A., and M. Bagshaw. 1974. The effect of serial correlation on the performance of CUSUM tests. Technometrics 16 (1):103–12. doi:10.1080/00401706.1974.10489155.
  • Kalgonda, A. A., and S. R. Kulkarni. 2004. Multivariate quality control chart for autocorrelated processes. Journal of Applied Statistics 31 (3):317–27. doi:10.1080/0266476042000184000.
  • Kim, J., M. K. Jeong, and E. A. Elsayed. 2017a. Monitoring multistage processes with autocorrelated observations. International Journal of Production Research 55 (8):2385–96. doi:10.1080/00207543.2016.1247996.
  • Kim, S., M. K. Jeong, and E. A. Elsayed. 2017b. Generalized smoothing parameters of multivariate EWMA control chart. IISE Transactions 49 (1):58–69. doi:10.1080/0740817X.2016.1198509.
  • Kramer, H. G., and L. Schmid. 1997. EWMA charts for multivariate time series. Sequential Analysis 16 (2):131–54. doi:10.1080/07474949708836378.
  • Laungrungrong, B., C. M. Borror, and D. C. Montgomery. 2014. A one-sided MEWMA control chart for Poisson-distributed data. International Journal of Data Analysis Techniques and Strategies 6 (1):15–42. doi:10.1504/IJDATS.2014.059013.
  • Lee, M. 2010. Multivariate EWMA control chart with adaptive sample sizes. Communications in Statistics - Simulation and Computation 39 (8):1548–61. doi:10.1080/03610918.2010.507897.
  • Leoni, R. C., M. A. G. Machado, and A. F. B. Costa. 2016. The T2 chart with mixed samples to control bivariate autocorrelated processes. International Journal of Production Research 54 (11):3294–310. doi:10.1080/00207543.2015.1102983.
  • Lin, W. S., and B. M. Adams. 1996. Combined control charts for forecast-based monitoring schemes. Journal of Quality Technology 28 (3):289–301. doi:10.1080/00224065.1996.11979679.
  • Lowry, C. A., W. H. Woodall, C. W. Champ, and S. E. Rigdon. 1992. A multivariate exponentially weighted moving average control chart. Technometrics 34 (1):46–53. doi:10.2307/1269551.
  • Lu, C. W., and M. R. Reynolds. Jr, 1999. Control charts for monitoring the mean and variance of autocorrelated processes. Journal of Quality Technology 31 (3):259–74. doi:10.1080/00224065.1999.11979925.
  • Lu, C. W., and M. R. Reynolds. Jr, 2001. CUSUM charts for monitoring an autocorrelated process. Journal of Quality Technology 33 (3):316–34. doi:10.1080/00224065.2001.11980082.
  • Lucas, J. M., and M. S. Saccucci. 1990. Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics 32 (1):1–12. doi:10.1080/00401706.1990.10484583.
  • Mahmoud, M. A., and P. E. Maravelakis. 2010. The performance of the MEWMA control chart when parameters are estimated. Communications in Statistics - Simulation and Computation 39 (9):1803–17. doi:10.1080/03610918.2010.518269.
  • Pan, X. 2005. Notes on shift effects for T2-type charts on multivariate ARMA residuals. Computers & Industrial Engineering 49 (3):381–92. doi:10.1016/j.cie.2005.07.001.
  • Prabhu, S. S., and G. C. Runger. 1997. Designing a multivariate EWMA control chart. Journal of Quality Technology 29 (1):8–15. doi:10.1080/00224065.1997.11979720.
  • Roberts, S. 1959. Control chart tests based on geometric moving averages. Technometrics 1 (3):239–50. doi:10.1080/00401706.1959.10489860.
  • Runger, G. C. 1996. Multivariate statistical process control for autocorrelated processes. International Journal of Production Research 34 (6):1715–24. doi:10.1080/00207549608904992.
  • Shu, L., D. W. Apley, and F. Tsung. 2002. Autocorrelated process monitoring using triggered cuscore charts. Quality and Reliability Engineering International 18 (5):411–21. doi:10.1002/qre.492.
  • Superville, C. R., and B. M. Adams. 1994. An evaluation of forecast-based quality control schemes. Communications in Statistics - Simulation and Computation 23 (3):645–61. doi:10.1080/03610919408813191.
  • Vanhatalo, E., and M. Kulahci. 2015. The effect of autocorrelation on the Hotelling T2 control chart. Quality and Reliability Engineering International 31 (8):1779–96. doi:10.1002/qre.1717.
  • Wardell, D. G., H. Moskowitz, and R. D. Plante. 1994. Run-length distributions of special-cause control charts for correlated processes. Technometrics 36 (1):3–17. doi:10.1080/00401706.1994.10485393.
  • Yu, J., and J. Liu. 2011. Lrprob control chart based on logistic regression for monitoring mean shifts of auto-correlated manufacturing processes. International Journal of Production Research 49 (8):2301–26. doi:10.1080/00207541003694803.
  • Zhang, N. F. 1998. A statistical control chart for stationary process data. Technometrics 40 (1):24–38. doi:10.1080/00401706.1998.10485479.
  • Zhang, N. F. 2000. Statistical control charts for monitoring the mean of a stationary process. Journal of Statistical Computation and Simulation 66 (3):249–58. doi:10.1080/00949650008812025.

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