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

Javed, Hina; Ismail, Muhammad; Saeed, Nadia

Javed, Hina; Ismail, Muhammad; Saeed, Nadia.

Afiliación

Javed H; College of Statistical Sciences, University of the Punjab, Lahore Pakistan.
Ismail M; COMSATS University Islamabad Lahore, Campus Lahore Pakistan.
Saeed N; College of Statistical Sciences, University of the Punjab, Lahore Pakistan.

Heliyon ; 10(14): e34424, 2024 Jul 30.

Article en En | MEDLINE | ID: mdl-39149066

ABSTRACT

ABSTRACT

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.

Palabras clave

Average run length; EEWMA; EWMA; NEEWMA; Normal distribution; SPC

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

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