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On the performance of the adaptive EWMA chart for monitoring time between events.

Authors :
Hu, XueLong
Castagliola, Philippe
Zhong, JianLan
Tang, AnAn
Qiao, YuLong
Source :
Journal of Statistical Computation & Simulation. Mar2021, Vol. 91 Issue 6, p1175-1211. 37p.
Publication Year :
2021

Abstract

In high-quality processes, events related to non-quality rarely occur and the times between these events (TBE) is likely to follow a skewed distribution like the gamma distribution. In order to monitor TBE data, an Adaptive Exponential Weighted Moving Average (AEWMA) control chart is proposed in this paper. This chart is designed to perform well over a range of shifts instead of being only efficient for a particular shift. An extensive performance analysis shows that, for most shifts, the Average Run Length (ARL) of the proposed chart performs better than other already existing control charts. In order to help the quality practitioner, some guidelines for choosing the most effective scheme in practice are provided. Finally, an illustrative example of the proposed scheme is also presented. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00949655
Volume :
91
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Statistical Computation & Simulation
Publication Type :
Academic Journal
Accession number :
149693390
Full Text :
https://doi.org/10.1080/00949655.2020.1843654