Optimization of univariate and multivariate exponentially weighted moving-average control charts using genetic algorithms

Authors:
Francisco Aparisi;J. Carlos García-Díaz
Affiliations:
Departamento de Estadística e Investigación Operativas Aplicadas y Calidad, Universidad Politécnica de Valencia, Valencia, Camino de Vera s/n. 46071 Valencia, Spain;Departamento de Estadística e Investigación Operativas Aplicadas y Calidad, Universidad Politécnica de Valencia, Valencia, Camino de Vera s/n. 46071 Valencia, Spain
Venue:
Computers and Operations Research
Year:
2004

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Abstract

Exponentially weighted moving-average (EWMA) and multivariate EWMA (MEWMA) process control charts can be applied to detect small changes in statistical process control efficiently. This paper presents a software program developed in Windows environment for the optimal design of the EWMA and MEWMA chart parameters, to protect the process in the case of shifts of given size. Optimization has been done using genetic algorithms.