An enhanced EWMA-t control chart for monitoring the process mean

Abdul Haq, Zain Ul Abidin and Michael B. C. Khoo

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 6, 1333-1350

Abstract: The exponentially weighted moving average (EWMA) control chart with the sample mean X‾$\overline{X}$ (EWMA-X‾$\overline{X}$) is widely recognized as a competent tool to detect small and moderate shifts in the mean of a normally distributed process. One shortcoming of the EWMA-X‾$\overline{X}$ chart is that it triggers an out-of-control signal when the process standard deviation is not stable. An alternative to the EWMA-X‾$\overline{X}$ chart is the EWMA-t chart. Unlike the EWMA-X‾$\overline{X}$ chart, the EWMA-t chart is robust to the changes in the process standard deviation. In this paper, we propose an auxiliary information-based (AIB) EWMA-t chart for monitoring the process mean, which requires information on the quality characteristic under study and any correlated auxiliary characteristic, named the AIB-EWMA-t chart. The Monte Carlo simulation method is used to compute the run length profiles of the proposed control chart. It is shown that the AIB-EWMA-t chart is uniformly and substantially better than the existing EWMA-t chart. Moreover, the AIB-EWMA-t chart could be used as an efficient alternative to the existing AIB-EWMA mean chart when the process standard deviation is unstable. An example is also used to demonstrate the implementation of the proposed and existing control charts.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2018.1429631 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:48:y:2019:i:6:p:1333-1350

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2018.1429631

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().