New extended exponentially weighted moving average control chart for monitoring process mean

被引：4

作者：

Javed, Hina ^{[1
]}

Ismail, Muhammad ^{[2
]}

Saeed, Nadia ^{[1
]}

机构：

[1] Univ Punjab, Coll Stat Sci, Lahore, Pakistan

[2] COMSATS Univ Islamabad Lahore, Lahore, Pakistan

来源：

HELIYON | 2024年 / 10卷 / 14期

关键词：

Average run length; EWMA; EEWMA; NEEWMA; SPC; Normal distribution; PERIODIC-SOLUTION;

D O I：

10.1016/j.heliyon.2024.e34424

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In this article, we develop a new control chart based on the Exponentially Weighted Moving Average (EWMA) statistic, termed the New Extended Exponentially Weighted Moving Average (NEEWMA) statistic, designed to recognize slight changes in the process mean. We derive expressions for the mean and variance of the NEEWMA statistic, ensuring an unbiased estimation of the mean, with simulation results showing lower variance compared to traditional EWMA charts. Evaluating its performance using Average Run Length (ARL), our analysis reveals that the NEEWMA control chart outperforms EWMA and Extended EWMA (EEWMA) charts in swiftly recognizing shifts in the process mean. Illustrating its operational methodology through Monte Carlo simulations, an illustrative example using practical data is also provided to showcase its effectiveness.

引用

页数：13

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