Adegoke, N.A., Abbasi, S.A., Dawod, A.B.A., & Pawley, M.D.M. (2019). Enhancing the performance of the EWMA control chart for monitoring the process mean using auxiliary information. Quality and Reliability Engineering International, 35(4), 920-933.
Aslam, M., Al-Marshadi, A.H., & Jun, C.H. (2017). Monitoring process mean using generally weighted moving average chart for exponentially distributed characteristics. Journal of Statistical Computation and Simulation, 46(5), 3712-3722.
Bag, M., Gauri, S.K., & Chakraborty, S. (2012). Feature-based decision rules for control charts pattern recognition: A comparison between CART and QUEST algorithm. International Journal of Industrial Engineering Computations, 3(2), 199-210.
Black, G., Smith, J., & Wells, S. (2011). The impact of Weibull data and autocorrelation on the performance of the Shewhart and exponentially weighted moving average control charts. International Journal of Industrial Engineering Computations, 2(3), 575-582.
Chakraborty, N., Chakraborti, S., Human, S.W., & Balakrishnan, N. (2016). A generally weighted moving average signed rank control chart. Quality and Reliability Engineering International, 32(8), 2835–2845.
Chakraborty, N., Human, S.W., & Balakrishnan, N. (2017). A generally weighted moving average chart for time between events. Communications in Statistics – Simulation and Computation, 46(10), 7790-7817.
Chakraborty, N., Human, S.W., & Balakrishnan, N. (2018). A generally weighted moving average exceedance chart. Journal of Statistical Computation and Simulation, 88(9), 1759-1781.
Haq, A. (2019). A maximum adaptive exponentially weighted moving average control chart for monitoring process mean and variability. Quality Technology & Quantitative Management, https://doi.org/ 10.1080/16843703.2018.1530181.
Haridy, S., Shamsuzzaman, M., Alsyouf, I., & Mukherjee A. (2019). An improved design of exponentially weighted moving average scheme for monitoring attributes. International Journal of Production Research, https://doi.org/ 10.1080/00207543.2019.1605224
Jensen, W.A., Jones-Farmer, L.A., Champ, C.W., & Woodall, W.H. (2006). Effects of parameter estimation on control chart properties: A literature review. Journal of Quality Technology, 38(4), 349-364.
Karakani, H.M., Human, S.W., & van Niekerk, J. (2019). A double generally weighted moving average exceedance control chart. Quality and Reliability Engineering International, 35(1), 224-245.
Li, S.Y., Tang, L.C., & Ng, S.H. (2010). Nonparametric CUSUM and EWMA control charts for detecting mean shifts. Journal of Quality Technology, 42(2), 209-226.
Lim, S.A.H., Antony, J., He, Z., & Arshed, N. (2017). Critical observations on the statistical process control implementation in the UK food industry. International Journal of Quality & Reliability Management, 34(5), 684-700.
Lu, S.L. (2015). An extended nonparametric exponentially weighted moving average sign control chart. Quality and Reliability Engineering International, 31(1), 3–13.
Lu, S.L. (2018). Nonparametric double generally weighted moving average sign charts based on process proportion. Communications in Statistics –Theory and Methods, 47(11), 2684-2700.
Malela-Majika, J.C., & Rapoo, E.M. (2016). Distribution-free CUSUM and EWMA control charts based on the Wilcoxon rank-sum statistic using ranked set sampling for monitoring mean shifts. Journal of Statistical Computation and Simulation, 86(16), 3715-3734.
Montgomery, D.C. (2005). Introduction to Statistical Quality Control, 5th ed. Wiley, New York.
Roberts, S.W. (1959). Control chart tests based on geometric moving averages. Technometrics, 1(3), 239–250.
Ruggeri, F., Kenett, R.S., & Faltin, F.W. (2007). Exponentially weighted moving average (EWMA) control chart. In Encyclopedia of Statistics in Quality and Reliability. John Wiley & Sons: Hoboken, New Jersey, 2, 633-639.
Sheu, S.H., & Hsieh, Y.T. (2009). The extended GWMA control chart. Journal of Applied Statistics, 36(2), 135-147.
Sheu, S.H., & Lin, T.C. (2003). The generally weighted moving average control chart for detecting small shifts in the process mean. Quality Engineering, 16(2), 209–231.
Sheu, S.H., & Yang, L. (2006). The generally weighted moving average control chart for monitoring the process median. Quality Engineering, 18(3), 333–344.
Shongwe, S.C., & Graham, M.A. (2017). Synthetic and runs-rules charts combined with an X ̅ chart: Theoretical discussion. Quality and Reliability Engineering International, 35(1), 7-35.
Simoglou, A, Martin, E.B., Morris, A.J., Wood, M., & Jones, G.C. (1997). Multivariate statistical process control in chemicals manufacturing. International Federation of Automatic Control (IFAC) Proceedings Volumes, 30(18), 21-28.
Sukparungsee, S. (2018). Robustness of the generally weighted moving average signed-rank control chart for monitoring a shift of skew processes. Matter: International Journal of Science and Technology, 4(3), https://doi.org/10.20319/mijst.2018.43.125137.
Tai, S., Lin, C., & Chen, Y. (2009). Design and implementation of the extended exponentially weighted moving average control charts. In Proceedings of the 2009 International Conference on Management and Service Science, IEEE Xplore, (MASS) (October 2009) pp. 1-4.
Teh, S.Y., Khoo, M.B.C., & Wu, Z. (2012). Monitoring process mean and variance with a single generally weighted moving average chart. Communications in Statistics –Theory and Methods, 41(12), 2221-2241.
Teh, S.Y., Khoo, M.B.C., Hong, K.H., & Soh, K.L. (2014). A comparative study of the median run length (MRL) performance of the Max-DEWMA and SS-DEWMA control charts. Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management, Bali, Indonesia, January.
Wilcoxon, F., Individual comparisons by ranking methods, Biometrics, 1(6), 80-83.
Zhang, M., Megahed, F.M., & Woodall, W.H. (2014). Exponential CUSUM charts with estimated control limits. Quality and Reliability Engineering International, 30(2), 275-286.