Paper Info
Title
Dual multivariate CUSUM charts with auxiliary information for process mean
Abstract
It is customary to increase the sensitivity of a control chart using an efficient estimator of the underlying process parameter which is being monitored. In this paper, using an auxiliary information-based (AIB) mean estimator, we propose dual multivariate CUSUM (DMCUSUM) and mixed DMCUSUM (MDMCUSUM) charts, called the AIB-DMCUSUM and AIB-MDMCUSUM charts, with and without fast initial response features for monitoring the mean vector of a multivariate normally distributed process. The DMCUSUM chart combines two similar-type multivariate CUSUM (MCUSUM) charts while the MDMCUSUM chart combines two different-type MCUSUM charts, into a single chart. The objective of two multivariate subcharts in the DMCUSUM/MDMCUSUM chart is to simultaneously detect small-to-moderate and moderate-to-large shifts in the process mean vector. Monte Carlo simulations are used to compute the run length characteristics, including the average run length (ARL), extra quadratic loss, and integral of the relative ARL. Based on detailed run length comparisons, it turns out that the AIB-DMCUSUM and AIB-MDMCUSUM charts uniformly and substantially outperform the DMCUSUM and MDMCUSUM charts when detecting different sizes of shift in the process mean vector. A real dataset is used to explain the implementation of proposed AIB multivariate charts.
Year
DOI
Venue
2020
10.1002/qre.2604
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Keywords
DocType
Volume
average run length,dual control chart,MCUSUM,Monte Carlo simulation,process mean,statistical process control
Journal
36.0
Issue
ISSN
Citations 
3.0
0748-8017
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Abdul Haq16318.42
Tahir Munir200.34
Burhan Ali Shah300.34