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Herein, we present a new control chart called the mixed double moving average-cumulative sum control chart (DMA-CUSUM: MDC) used for detecting shifts in the process mean when symmetrically and asymmetrically distributed. The performance of the MDC chart is compared with shewhart, cumulative sum (CUSUM), double moving average (DMA) and mixed cumulative sum-double moving average (CUSUM-DMA: MCD) control charts by using average run length (ARL) and median run length (MRL) with the monte carlo simulation (MC). The research results show that the proposed (MDC) control chart was more efficient than the Shewhart, CUSUM, DMA and MCD charts for all distributions tested. We apply the MDC chart to real sets of data: I) the tensile data of single carbon fiber and II) the survival times of guinea pigs infected with virulent bacilli.
W. A. Shewhart, “Statistical control,” in Economic Control of Quality Manufactured Product, vol. 11, New York: D. Van Nostrand Company, 1931, p. 145.
E. S. Page, “Continuous inspection schemes,” Biometrika, vol. 41, no. 1–2, pp. 100–115, Jun. 1954, doi: 10.1093/biomet/41.1-2.100.
B. C. Khoo, “A moving average control chart for monitoring the fraction non-conforming,” Quality and Reliability Engineering International, vol. 20, no. 6, pp. 617–635, Oct. 2004, doi: 10.1002/qre.576.
B. C. Khoo and V. H. Wong, “A double moving average control chart,” Communications in Statistics – Simulation and Computation, vol. 37, no. 8, pp. 1696–1708, Oct. 2008, doi: 10.1080/03610910701832459.
B. Zaman, M. Riaz, N. Abbas, and R. J. M. M. Does, “Mixed cumulative sum-exponentially weighted moving average control charts: An efficient way of monitoring process location,” Quality and Reliability Engineering International, vol. 31, no. 8, pp. 1407–1421, Dec. 2015, doi: 10.1002/qre.1678.
M. Aslam, W. Gui, N. Khan, and C. -H. Jun, “Double moving average-EWMA control chart for exponentially distributed quality,” Communications in Statistics – Simulation and Computation, vol. 46, no. 9, pp. 7351–7364, Apr. 2017, doi: 10.1080/03610918.2016.1236955.
J. O. Ajadi and M. Riaz, “Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring,” Communications in Statistics – Theory and Methods, vol. 46, no. 14, pp. 6980–6993, Mar. 2017, doi: 10.1080/03610926.2016.1139132.
N. Abbas, I. A. Raji, M. Riaz, and K. A. L. -Ghamdi, “On designing mixed EWMA Dual-CUSUM chart with applications in petro-chemical industry,” IEEE Access, vol. 6, pp. 78931–78946, Dec. 2018, doi: 10.1109/ ACCESS.2018.2885598.
R. Thitisoowaranon, S. Sukparungsee, and Y. Areepong, “A mixed cumulative sum-Tukey’s control chart for detecting process dispersion,” The Journal of KMUTNB, vol. 29, no. 3, pp. 507–517, Jul.-Sep. 2019, doi: 10.14416/ j.kmutnb.2019.04.004.
C. C. Alves, A. C. Konrath, E. Henning, O. M. F. C. Walter, E. P. Paladini, T. A. Oliveria, and A. Oliveira, “The mixed CUSUM-EWMA (MCE) control chart as a new alternative in the monitoring of a manufacturing process,” Brazillian Journal of Operations & Production Management, vol. 6, no. 1, pp. 1–13, Mar. 2019, doi: 10.14488/BJOPM.2019.v16.n1.a1.
S. Hussain, X. Wang, S. Ahmand, and M. Riaz, “On a class of mixed EWMA-CUSUM median control charts for process monitoring,” Quality and Reliability Engineering International, vol. 36, no. 3, pp. 910–946, Apr. 2020, doi: 10.1002/qre.2608.
M. Abid, S. Mei, H. Z. Nazir, and M. Riaz, “A mixed HWMA-CUSUM mean chart with an application to manufacturing process,” Quality and Reliability Engineering International, vol. 37, no. 2, pp. 618–631, Mar. 2021, doi: 10.1002/ qre.2752.
S. Phantu and S. Sukparungsee, “A mixed double exponentially weighted moving average-Tukey’s control chart for monitoring of parameter change,” Thailand Statistician, vol. 18, no. 4, pp. 392–402, Oct. 2020.
N. Saengsura, S. Sukparungsee, and Y. Areepong, “Mixed moving average-cumulative sum control chart for monitoring parameter change,” Intelligent Automation & Soft Computing, vol. 31, no. 1, pp. 635–647, 2022, doi: 10.32604/iasc.2022.019997.
S. Sukparungsee, N. Saengsura, Y. Areepong, and S. Phantu, “Mixed Tukey-double moving average for monitoring of process mean,” Thailand Statistician, vol. 19, no. 4, pp. 885–865, Oct. 2021.
D. C. Montgomery, Introduction to Statistical Quality Control Case Study, 6th ed. New York: John Wiley and Sons, 2009.
S. Sukparungsee, Y. Areepong, and R. Taboran, “Exponentially weighted moving averagemoving average charts for monitoring the process mean,” PLOS ONE, vol. 15, no. 2, 2020, doi: 10.1371/journal.pone.0228208.
F. F. Gan, “An optimal design of cumulative sum control charts based on median run length,” Communications in Statistics - Simulation and Computation, vol. 23, no. 2, pp. 485–503, 1994, doi: 10.1080/03610919408813183.
R. Taboran, S. Sukparungsee, and Y. Areepong, “Design of a new Tukey MA-DEWMA control chart to monitor process and its applications,” IEEE Access, vol. 9, pp. 102746–102757, Jul. 2021, doi: 10.1109/ACCESS.2021.3098172.
B. Efron, “Logistic regression survival analysis and the Kaplan-Meier curve,” Journal of the American Statistical Association, vol. 83, no. 402, pp. 414–425, 1988, doi: 10.2307/2288857.
R. Taboran, S. Sukparungsee, and Y. Areepong, “Mixed moving average-exponentially weighted moving average control charts for monitoring of parameter change,” in International MultiConference of Engineers and Computer Scientists, 2019, pp. 411–415.