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

被引：40

作者：

Aparisi, F ^{[1
]}

Garcia-Diaz, JC ^{[1
]}

机构：

[1] Univ Politecn Valencia, Dept Estadist & Invest Operat Aplicadas & Calidad, Valencia 46071, Spain

来源：

COMPUTERS & OPERATIONS RESEARCH | 2004年 / 31卷 / 09期

关键词：

statistical process control; EWMA and MEWMA charts; optimization; genetic algorithms;

D O I：

10.1016/S0305-0548(03)00099-6

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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. (C) 2003 Elsevier Ltd. All rights reserved.

引用

页码：1437 / 1454

页数：18

共 33 条

[1] Hotelling's T-2 control chart with adaptive sample sizes [J].