A multivariate EWMA control chart for skewed populations using weighted variance method

This article proposes Multivariate Exponential Weighted Moving Average control chart for skewed population using heuristic Weighted Variance (WV) method, obtained by decomposing the variance into the upper and lower segments according to the direction and degree of skewness.This method adjusts the...

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Bibliographic Details
Main Authors: AMA, Atta, MHA, Shoraim, Syed Yahaya, Sharipah Soaad
Format: Article
Language:English
Published: IRJSE 2014
Subjects:
Online Access:http://repo.uum.edu.my/20175/1/IRJSE%202014%202%206%20191-202.pdf
http://repo.uum.edu.my/20175/
http://www.irjse.in/volume2(6).html
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Institution: Universiti Utara Malaysia
Language: English
Description
Summary:This article proposes Multivariate Exponential Weighted Moving Average control chart for skewed population using heuristic Weighted Variance (WV) method, obtained by decomposing the variance into the upper and lower segments according to the direction and degree of skewness.This method adjusts the variance-covariance matrix of quality characteristics.The proposed chart, called WV-MEWMA hereafter, reduces to standard multivariate Exponential Weighted Moving Average control chart (standard MEWMA) when the underlying distribution is symmetric.In control and out-of-control ARLs of the proposed WV-MEWMA control chart are compared with those of the weighted standard deviation Exponential Weighted Moving Average (WSD-MEWMA) and (standard MEWMA) control charts for multivariate normal, lognormal and gamma distributions. In general, the simulation results show that the performance of the proposed WV-MEWMA chart is better than WSD-MEWMA and Standard MEWMA charts when the underlying distributions are skewed.