A Double Multivariate Homogeneously Weighted Moving Average Control Chart: An Extension Work

Document Type : Original Article

Authors
Department of Statistics, University of Nigeria, Nsukka, Enugu State, Nigeria.
10.22034/jirss.2025.2013301.1039
Abstract
This work extends an existing multivariate homogeneously weighted moving average (MHWMA)-control chart to a multivariate double homogeneously weighted moving average (MDHWMA)-control chart aimed at a more efficient monitoring of the process mean vector. Like the MHWMA-control chart, the MDHWMA-control chart statistic assigns a specific weight to the current observation, and the remaining weight is evenly assigned among the previous observations but unlike the MHWMA-control chart, the MDHWMA-control chart statistic utilizes the information contained in the observations twice. We present the design structure of the MDHWMA-control chart and on the basis of the average, standard deviation of the average and the median run lengths (ARL, SDRL & MRL) compare the performance with the MHWMA-control chart in relation to Hotelling's \chi^{2}-chart, multivariate cumulative sum (MCUSUM)-chart and the multivariate exponentially moving average (MEWMA)-chart. The comparison showed that the proposed (MDHWMA)-control chart has a better performance than the competing charts, especially for small shifts
Keywords
Subjects

Abbas N. Homogeneously weighted moving average control chart with an application in substrate manufacturing process. Computers and Industrial Engineering. 2018;120(2):460–470. https://doi.org/10.1016/j.cie.2018.05.027.
Abbas N, Riaz M, Does RJMM. Mixed exponentially weighted moving averagecumulative sum charts for process monitoring. Quality and Reliability Engineering International. 2013;29(3):345–356. https://doi.org/10.1002/qre.1391.
Abbas Z, Nazir HZ, Akhtar N, Riaz M, Abid M. On developing an exponentially weighted moving average chart under progressive setup: An efficient approach to manufacturing processes. Quality and Reliability Engineering International. 2020;36(8):2569–2591. https://doi.org/10.1002/qre.2660.
Abbasi SA, Riaz M, Miller A, Ahmad S, Nazir HZ. EWMA dispersion control charts for normal and non-normal processes. Quality and Reliability Engineering International. 2015;31(8):1691–1704. https://doi.org/10.1002/qre.1660.
Abid M, Shabbir A, Nazir HZ, Sherwani RAK, Riaz M. A double homogeneously weighted moving average control chart for monitoring of the process mean. Quality and Reliability Engineering International. 2020;36(1):1513–1527. https://doi. org/10.1002/qre.2591.
Adegoke NA, Abbasi SA, Smith ANH, Anderson MJ, Pawley MDM. A multivariate homogeneously weighted moving average control chart. IEEE Access. 2019;7(1):9586– 9597. https://doi.org/10.1109/ACCESS.2019.2890780.
Aslam M, Bhattacharya R, Aldosari MS. Design of control chart in presence of hybrid censoring scheme. IEEE Access. 2018;6(1):14895–14907. https://doi.org/10.1109/ ACCESS.2018.2817583.
Crosier RB. Multivariate generalizations of cumulative sum quality-control schemes. Technometrics. 1988;30(3):291–303. https://doi.org/10.1080/00401706.1988. 10488407.
Hawkins DM, Maboudou-Tchao EM. Self-starting multivariate exponentially weighted moving average control charting. Technometrics. 2007;49(2):199–209. https://doi. org/10.1198/004017007000000125. 
Hotelling H. Multivariate quality control illustrated by the air testing of sample bombsights. In: Eisenhart MWHC, Wallis WA, editors. Techniques of Statistical Analysis. New York, NY, USA: McGraw-Hill; 1947. p. 111–184.
Human SW, Kritzinger P, Chakraborti S. Robustness of the EWMA control chart for individual observations. Journal of Applied Statistics. 2011;38(10):2071–2087. https: //doi.org/10.1080/02664763.2010.545117.
Hunter JS. The exponentially weighted moving average. Journal of Quality Technology. 1986;18(4):203–210.
Kramer HG, Schmid W. EWMA charts for multivariate time series. Sequential Analysis. 1997;16(2):131–154. https://doi.org/10.1080/07474949708836320.
Letshedi TI, Malela-Majika JC, Shongwe SC. New extended distribution-free homogeneously weighted monitoring schemes for monitoring abrupt shifts in the location parameter. PLOS ONE. 2022;17(1):e0262840. https://doi.org/10.1371/journal. pone.0262840.
Lowry CA, Woodall WH, Champ CW, Rigdon SE. A multivariate exponentially weighted moving average control chart. Technometrics. 1992;34(1):46–53. https: //doi.org/10.1080/00401706.1992.10485232.
Lucas JM. Combined Shewhart-CUSUM quality control schemes. Journal of Quality Technology. 1982;14(2):51–59.
Lucas JM, Saccucci MS. Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics. 1990;32(1):1–12. https://doi.org/10. 1080/00401706.1990.10484583.
Luke P, Jean C, Malela-Majika JC, Schalk H, Philippe C. A new multivariate extended homogeneously weighted moving average monitoring scheme incorporated with a support vector machine. Quality and Reliability Engineering International. 2023;39(6):2454–2475. https://doi.org/10.1002/qre.3245.
Page ES. Continuous inspection schemes. Biometrika. 1954;41(1–2):100–115. https: //doi.org/10.1093/biomet/41.1-2.100.
Park J, Jun CH. A new multivariate EWMA control chart via multiple testing. Journal of Process Control. 2015;26(1):51–55. https://doi.org/10.1016/j.jprocont.2014. 10.003.
Pignatiello JJ, Runger GC. Comparisons of multivariate CUSUM charts. Journal of Quality Technology. 1990;22(3):173–186.
Roberts SW. Control chart tests based on geometric moving averages. Technometrics. 1959;1(3):239–250. https://doi.org/10.1080/00401706.1959.10489860. 
Saber A, Zameer A, Hafiz ZN, Riaz M, Xingfa Z, Yuan L. On developing sensitive nonparametric mixed control charts with application to manufacturing industry. Quality and Reliability Engineering International. 2021;2021:1–25. https: //doi.org/10.1002/qre.2898.
Seif A, Moghadam MB, Faraz A, Heuchenne C. Statistical merits and economic evaluation of T2 control charts with the VSSC scheme. Arabian Journal for Science and Engineering. 2011;36(7):1461–1470. https://doi.org/10.1007/s13369-011-0139-z.
Shamma SE, Shamma AK. Development and evaluation of control charts using double exponentially weighted moving averages. International Journal of Quality and Reliability Management. 1992;9(6):18–25. https://doi.org/10.1108/ 02656719210019481.
Testik MC, Runger GC, Borror CM. Robustness properties of multivariate EWMA control charts. Quality and Reliability Engineering International. 2003;19(1):31–38. https://doi.org/10.1002/qre.525.
Yumin L. An improvement for MEWMA in multivariate process control. Computers and Industrial Engineering. 1996;31(3):779–781. https://doi.org/10.1016/ 0360-8352(96)00218-3.
Zaman B, Abbas N, Does RJMM. Mixed cumulative sum exponentially weighted moving average control charts. Quality and Reliability Engineering International. 2014;31(8):1407–1421. https://doi.org/10.1002/qre.1651. 
Volume 24, Issue 1
June 2025
Pages 139-156

  • Receive Date 10 October 2023
  • Revise Date 01 October 2025
  • Accept Date 12 October 2025