Paper Info
Title
New efficient exponentially weighted moving average variability charts based on auxiliary information
Abstract
Control chart is a well-known tool for monitoring the performance of an ongoing process. The variability of a process is an important parameter that may deteriorate the process performance if it is not taken care on time. In this study, we have proposed some new auxiliary information-based exponentially weighted moving average (EWMA) charts for improved monitoring of process variability. We employed auxiliary information in some useful forms including ratio, regression, power ratio, ratio exponential, ratio regression, power ratio regression, and ratio exponential regression estimators. The performance of the newly developed charts is evaluated and compared with some existing charts (viz., the NEWMA, the Improved R, the Synthetic R, and the classical R charts), using some useful measures such as average run length (ARL), extra quadratic loss, and relative ARL. The comparative analysis revealed that the proposed charts outperform their counterparts, especially when there is a strong relationship between the study and the auxiliary variables. Finally, an illustrative example is provided for the monitoring of air quality data.
Year
DOI
Venue
2020
10.1002/qre.2692
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Keywords
DocType
Volume
auxiliary variables,average run length,control charts,dispersion parameter,EWMA chart,extra quadratic loss
Journal
36.0
Issue
ISSN
Citations 
7.0
0748-8017
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Saddam Akber Abbasi112518.72
Muhammad Riaz256.92
Shabbir Ahmad35810.69
Ridwan A. Sanusi4102.44
Muhammad Abid54610.69