The Mixed MEWMA and MCUSUM Control Chart Design of Efficiency Series Data of Production Quality Process Monitoring

Dodi Devianto (1), Maiyastri (2), Yudiantri Asdi (3), Sri Maryati (4), Surya Puspita Sari (5), Rahmat Hidayat (6)
(1) Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
(2) Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
(3) Department of Mathematics and Data Science, Universitas Andalas, Padang 25163, Indonesia
(4) Department of Economics, Universitas Andalas, Padang 25163, Indonesia
(5) Department of Statistics, Kalimantan Institute of Technology, Balikpapan 76127, Indonesia
(6) Department of Information Technology, Politeknik Negeri Padang, Padang 25164, Indonesia
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How to cite (IJASEIT) :
Devianto, Dodi, et al. “The Mixed MEWMA and MCUSUM Control Chart Design of Efficiency Series Data of Production Quality Process Monitoring”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 3, June 2024, pp. 841-6, doi:10.18517/ijaseit.14.3.19747.
A control chart is a crucial statistical tool for tracking the average quality of the dispersion. A more sensitive control chart is also developed to detect minor changes in the efficiency monitoring process, along with the times when using multivariate and mixed models. The well-known multivariate control chart was introduced as T2 Hotelling; then, to achieve better sensitivity in multivariable, a control chart design was developed for MEWMA and MCUSUM. To find a more sensitive multivariate control chart, it is proposed the control chart MCUSUM type I (MC I) and MCUSUM type II (MC II), and their combination of efficiency as the Mixed MEWMA-MCUSUM type I (MEC I), and the Mixed MEWMA-MCUSUM type II (MEC II). This study was carried out to assess which multivariate control chart is more sensitive by focusing on the ability of the control chart to detect more out-of-control observations in a single control phase. This study used data on the manufacture of wheat flour with 1,380 observations, 30 subgroups, and 46 observations per subgroup. Moisture, ash, and gluten are the quality-related manufacturing data variables used. This study aims to develop the best-mixed control chart design of efficiency for production and quality process monitoring of flour production. Based on the study's findings, the MEC I control chart was shown to be the most sensitive, and this study also demonstrates that it is more sensitive than other multivariate control charts.

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