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Explicit Formulas of Average Run Length for Triple Moving Average Control Chart to Monitor Changes in Mean Parameter of Normal and Non-normal Process

Apitad Kraichok, Yupaporn Areepong, Saowanit Sukparungsee

Abstract


In this research, a formula is presented for calculating the average run length of a triple moving average (TMA) control chart, which is used to measure control chart performance and determine control chart width. To apply appropriately to data in various processes, a TMA control chart is used to detect small changes in a process by finding the average value of the data over a specified period of time (w). However, determining measure control chart performance and control chart width is difficult because the formula for calculation is not created. The performance of the control charts is measured using the standard normal distribution probability properties and compared with the moving average (MA) control charts and the double moving average (DMA) control charts. The analysis results show that TMA is very effective at detecting small changes, when w is set to have a small value. The study determines that the data within the process are normally and non-normally distributed. Detecting changes on real data by TMA charts has the best detection performance compared to MA and DMA.

Keywords



[1]    W. A. Shewhart, Economic Control of Quality of manufactured Product. New York: D. Van Nostrand Company, Inc. 1931.

[2]    D. C. Montgomery, Introduction to Statistical Quality Control Case Study, 6th ed., New York: John Wiley and Sons, 2009.

[3]    E. S. Page, “Continuous inspection schemes,” Biometrika, vol. 41, pp. 100–144, 1954.

[4]    S. W. Roberts, “Control chart tests based on geometric moving average,” Technometrics, vol. 1, pp. 239–250, 1959.

[5]    S. W. Butler and J. A. Stefani, “Supervisory run-to-run control of a polysilicon gate etch using in situ ellipsometry,” IEEE Transaction on Semiconductor Manufacturing, vol. 7, pp. 193–201, 1994.

[6]    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.

[7]    Y. Areepong and S. Sukparungsee, “The closed-form formulas of average run length of moving average control chart for nonconforming for zero-inflated process,” Far East Journal of Mathematical Sciences, vol. 75, pp. 385–400, 2013.

[8]    C. Chananet, Y. Areepong, and S. Sukparungsee, “An approximate formula for ARL in moving average chart with ZINB data,” Thailand Statistician, vol. 13, pp. 209–222, 2015.

[9]    S. Sukparungsee and S. Phantu, “Explicit formulas of moving average control chart for zero modified geometric integer valued autoregressive process,” Applied Science and Engineering Progress, vol. 17, no. 1, 2024, Art. no. 6921, doi: 10.14416/j.asep.2023.09.004.

[10] A. A. Olatunde and J. O. Olaomi, “A moving average S control chart for monitoring process variability,” Quality Engineering, vol. 28, no. 2, pp. 212–219, 2016, doi: 10.1080/08982112.2015.

[11] I. S. Trianntafyllou and M. Ram, Statistical Modeling of Reliability Structures and Industrial Processes. Florida: CRC Press, 2022.

[12] 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. 855–865, 2021.

[13] M. B. C. Khoo and V. H. Wong, “A double moving average control chart,” Communication in Statistics – Simulation and Computation, vol. 37, pp. 1696–1708, 2008, doi: 10.1080/ 03610910701832459.

[14] Y. Areepong and S. Sukparungsee, “The closed-form formulas of average run length of moving average control chart for nonconforming for zero-inflated process,” Far East Journal of Mathematical Sciences, vol. 75, pp. 385–400,  2013.

[15] S. Phantu, Y. Areepong, and S. Sukparungsee, “Average run length formulas for mixed double moving average - exponentially weighted moving average control chart,” Science and Technology Asia, vol. 28, no.1, pp.77–89, 2023.

[16]  V. Alevizakos, K. Chatterjee, and C. Koukouvinos, “The triple exponentially weighted moving average control chart,” Quality Technology and Quantitative Management, vol. 18, no. 3, pp. 326–354, 2020, doi: 10.1080/16843703.2020. 1809063.

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DOI: 10.14416/j.asep.2024.09.012

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