Triple exponentially weighted moving average control charts without or with variable sampling interval for monitoring the coefficient of variation

References

• Page ES. Continuous inspection schemes. Biometrika. 1954;41(1-2):100–115. doi:10.1093/biomet/41.1-2.100
   Web of Science ®Google Scholar
• Roberts SW. Control chart tests based on geometric moving averages. Technometrics. 1959;1(3):239–250. doi:10.1080/00401706.1959.10489860
   Google Scholar
• Castagliola P, Celano G, Psarakis S. Monitoring the coefficient of variation using EWMA charts. J Qual Technol. 2011;43(3):249–265. doi:10.1080/00224065.2011.11917861
   Web of Science ®Google Scholar
• Castagliola P, Achouri A, Taleb H, et al. Monitoring the coefficient of variation using a variable sample size control chart. Int J Adv Manuf Technol. 2015;80(9):1561–1576. doi:10.1007/s00170-015-6985-6
   Web of Science ®Google Scholar
• Schwartz LH, Ginsberg MS, DeCorato D, et al. Evaluation of tumor measurements in oncology: use of film-based and electronic techniques. J Clin Oncol. 2000;18(10):2179–2184. doi:10.1200/JCO.2000.18.10.2179
   PubMed Web of Science ®Google Scholar
• Hamer AJ, Strachan JR, Black MM, et al. A new method of comparative bone strength measurement. J Med Eng Technol. 1995;19(1):1–5. doi:10.3109/03091909509030263
   PubMed Web of Science ®Google Scholar
• Reed GF, Lynn F, Meade BD. Use of coefficient of variation in assessing variability of quantitative assays. Clin Diagn Lab Immunol. 2002;9(6):1235–1239.
   PubMedGoogle Scholar
• Pang WK, Yu BW-T, Troutt MD, et al. A simulation-based approach to the study of coefficient of variation of dividend yields. Eur J Oper Res. 2008;189(2):559–569. doi:10.1016/j.ejor.2007.05.032
   Web of Science ®Google Scholar
• Ahn K-I. On the use of coefficient of variation for uncertainty analysis in fault tree analysis. Reliab Eng Syst Saf. 1995;47(3):229–230. doi:10.1016/0951-8320(94)00061-R
   Web of Science ®Google Scholar
• Gong J, Li Y. Relationship between the estimated weibull modulus and the coefficient of variation of the measured strength for ceramics. J Am Ceram Soc. 1999;82(2):449–452. doi:10.1111/j.1551-2916.1999.tb20084.x
   Web of Science ®Google Scholar
• Kang CW, Lee MS, Seong YJ, et al. A control chart for the coefficient of variation. J Qual Technol. 2007;39(2):151–158. doi:10.1080/00224065.2007.11917682
   Web of Science ®Google Scholar
• Hong E-P, Kang C-W, Baek J-W, et al. Development of CV control chart using EWMA technique. J Soc Korea Ind Syst. 2008;31(4):114–120.
   Google Scholar
• Calzada ME, Scariano SM. A synthetic control chart for the coefficient of variation. J Stat Comput Simul. 2013;83(5):853–867. doi:10.1080/00949655.2011.639772
   Web of Science ®Google Scholar
• Zhang J, Li Z, Chen B, et al. A new exponentially weighted moving average control chart for monitoring the coefficient of variation. Comput Ind Eng. 2014;78:205–212. doi:10.1016/j.cie.2014.09.027
   Web of Science ®Google Scholar
• Shu L, Jiang W. A new EWMA chart for monitoring process dispersion. J Qual Technol. 2008;40(3):319–331. doi:10.1080/00224065.2008.11917737
   Web of Science ®Google Scholar
• Zhang J, Li Z, Wang Z. Control chart for monitoring the coefficient of variation with an exponentially weighted moving average procedure. Qual Reliab Eng Int. 2018;34(2):188–202. doi:10.1002/qre.2247
   Web of Science ®Google Scholar
• Psarakis S. Adaptive control charts: recent developments and extensions. Qual Reliab Eng Int. 2015;31(7):1265–1280. doi:10.1002/qre.1850
   Web of Science ®Google Scholar
• Castagliola P, Achouri A, Taleb H, et al. Monitoring the coefficient of variation using a variable sampling interval control chart. Qual Reliab Eng Int. 2013;29(8):1135–1149. doi:10.1002/qre.1465
   Web of Science ®Google Scholar
• Yeong WC, Khoo MBC, Tham LK, et al. Monitoring the coefficient of variation using a variable sampling interval EWMA chart. J Qual Technol. 2017;49(4):380–401. doi:10.1080/00224065.2017.11918004
   Web of Science ®Google Scholar
• Tran PH, Heuchenne C. Monitoring the coefficient of variation using variable sampling interval CUSUM control charts. J Stat Comput Simul. 2021;91(3):501–521. doi:10.1080/00949655.2020.1819278
   Web of Science ®Google Scholar
• Ayyoub HN, Khoo MBC, Saha S, et al. Variable sampling interval EWMA chart for multivariate coefficient of variation. Commun Stat - Theory Methods. 2022;51(4):4617–4637.
   Google Scholar
• Jalilibal Z, Amiri A, Castagliola P, et al. Monitoring the coefficient of variation: a literature review. Comput Ind Eng. 2021;161:107600.
   Web of Science ®Google Scholar
• Shamma SE, Amin RW, Shamma AK. A double exponentially weigiited moving average control procedure with variable sampling intervals. Commun Stat Simul Comput. 1991;20(2-3):511–528. doi:10.1080/03610919108812969
   Web of Science ®Google Scholar
• Shamma S, Shamma AK. Development and evaluation of control charts using double exponentially weighted moving averages. Int J Qual Reliab Manag. 1992;9. doi:10.1108/02656719210018570
   Google Scholar
• Alevizakos V, Chatterjee K, Koukouvinos C. The triple exponentially weighted moving average control chart. Quality Technol Quant Manag. 2021;18(3):326–354. doi:10.1080/16843703.2020.1809063
   Web of Science ®Google Scholar
• Chatterjee K, Koukouvinos C, Lappa A. Monitoring process mean and variability with one triple EWMA chart. Commun Stat Simul Comput. 2022: 1–31. doi:10.1080/03610918.2022.2025835
   Web of Science ®Google Scholar
• Malela-Majika J-C, Shongwe SC, Chatterjee K, et al. Monitoring univariate and multivariate profiles using the triple exponentially weighted moving average scheme with fixed and random explanatory variables. Comput Ind Eng. 2022;163:107846. doi:10.1016/j.cie.2021.107846
   Web of Science ®Google Scholar
• Letshedi TI, Malela-Majika J-C, Castagliola P, et al. Distribution-free triple EWMA control chart for monitoring the process location using the Wilcoxon rank-sum statistic with fast initial response feature. Qual Reliab Eng Int. 2021;37(5):1996–2013. doi:10.1002/qre.2842
   Web of Science ®Google Scholar
• Iglewicz B, Myers RH, Howe RB. On the percentage points of the sample coefficient of variation. Biometrika. 1968;55(3):580–581. doi:10.1093/biomet/55.3.580
   Web of Science ®Google Scholar
• Breunig R. An almost unbiased estimator of the coefficient of variation. Econ Lett. 2001;70(1):15–19. doi:10.1016/S0165-1765(00)00351-7
   Web of Science ®Google Scholar
• Hu X, Zhang S, Zhou X, et al. The performance of double exponentially weighted moving average control charts for monitoring the coefficient of variation. Commun Stat Simul Comput. 2022. doi:10.1080/03610918.2022.2057539.
   Web of Science ®Google Scholar
• Barr DR, Sherrill ET. Mean and variance of truncated normal distributions. Am Stat. 1999;53(4):357–361.
   Web of Science ®Google Scholar
• Saccucci MS, Amin RW, Lucas JM. Exponentially weighted moving average control schemes with variable sampling intervals. Commun Stat Simul Comput. 1992;21(3):627–657. doi:10.1080/03610919208813040
   Web of Science ®Google Scholar
• Haq A, Akhtar S. Auxiliary information based maximum EWMA and DEWMA charts with variable sampling intervals for process mean and variance. Commun Stat – Theory Methods. 2022;51(12):3985–4005.
   Web of Science ®Google Scholar
• Reynolds MR, Amin RW, Arnold JC. CUSUM charts with variable sampling intervals. Technometrics. 1990;32(4):371–384. doi:10.1080/00401706.1990.10484721
   Web of Science ®Google Scholar
• Ryan AG, Woodall WH. Control charts for poisson count data with varying sample sizes. J Qual Technol. 2010;42(3):260–275. doi:10.1080/00224065.2010.11917823
   Web of Science ®Google Scholar
• Dickinson RM, Roberts DAO, Driscoll AR, et al. CUSUM charts for monitoring the characteristic life of censored weibull lifetimes. J Qual Technol. 2014;46(4):340–358. doi:10.1080/00224065.2014.11917976
   Web of Science ®Google Scholar
• Xu S, Jeske DR. Weighted EWMA charts for monitoring type I censored weibull lifetimes. J Qual Technol. 2018;50(2):220–230. doi:10.1080/00224065.2018.1436830
   Web of Science ®Google Scholar
• Thanwane M, Malela-Majika J-C, Castagliola P, et al. The effect of measurement errors on the performance of the homogenously weighted moving average X¯ monitoring scheme with estimated parameters. J Stat Comput Simul. 2021;91(7):1306–1330. doi:10.1080/00949655.2020.1850728
   Web of Science ®Google Scholar