Fuzzy exponentially weighted moving average control chart for univariate data with a real case application

被引：52

作者：

Senturk, Sevil ^{[1
]}

Erginel, Nihal ^{[2
]}

Kaya, Ihsan ^{[3
]}

Kahraman, Cengiz ^{[4
]}

机构：

[1] Anadolu Univ, Dept Stat, TR-26470 Eskisehir, Turkey

[2] Anadolu Univ, Dept Ind Engn, TR-26555 Eskisehir, Turkey

[3] Yildiz Tekn Univ, Dept Ind Engn, TR-34349 Istanbul, Turkey

[4] Istanbul Tech Univ, Dept Ind Engn, TR-34367 Istanbul, Turkey

来源：

APPLIED SOFT COMPUTING | 2014年 / 22卷

关键词：

Statistical process control; EWMA; Fuzzy control charts; Fuzzy EWMA; LINGUISTIC DATA; ALPHA-CUTS; CONSTRUCTION;

D O I：

10.1016/j.asoc.2014.04.022

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Statistical process control (SPC) is an approach to evaluate processes whether they are in statistical control or not. For this aim, control charts are generally used. Since sample data may include uncertainties coming from measurement systems and environmental conditions, fuzzy numbers and/or linguistic variables can be used to capture these uncertainties. In this paper, one of the most popular control charts, exponentially weighted moving average control chart (EWMA) for univariate data are developed under fuzzy environment. The fuzzy EWMA control charts (FEWMA) can be used for detecting small shifts in the data represented by fuzzy numbers. FEWMA decreases number of false decisions by providing flexibility on the control limits. The production process of plastic buttons is monitored with FEWMA in Turkey as a real application. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：1 / 10

页数：10

共 21 条

[1] Fuzzy multivariate exponentially weighted moving average control chart [J].