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AuthorRiaz, Muhammad
AuthorAbid, Muhammad
AuthorNazir, Hafiz Zafar
AuthorAbbasi, Saddam Akber
Available date2020-08-18T08:34:45Z
Publication Date2019
Publication NamePLoS ONE
ResourceScopus
ISSN19326203
URIhttp://dx.doi.org/10.1371/journal.pone.0225330
URIhttp://hdl.handle.net/10576/15666
AbstractControl charts play a significant role to monitor the performance of a process. Nonparametric control charts are helpful when the probability model of the process output is not known. In such cases, the sampling mechanism becomes very important for picking a suitable sample for process monitoring. This study proposes a nonparametric arcsine exponentially weighted moving average sign chart by using an efficient scheme, namely, sequential sampling scheme. The proposal intends to enhance the detection ability of the arcsine exponentially weighted moving average sign chart, particularly for the detection of small shifts. The performance of the proposal is assessed, and compared with its counterparts, by using some popular run length properties including average, median and standard deviation run lengths. The proposed chart shows efficient shift detection ability as compared to the other charts, considered in this study. A real-life application based on the smartphone accelerometer data-set, for the implementation of the proposed scheme, is also presented. - 2019 Riaz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
SponsorThis work was supported by King Fahd University of Petroleum and Minerals grant IN171016. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Languageen
PublisherPublic Library of Science
SubjectControl Charts
Average Run Length
Exponentially Weighted Moving Average
TitleAn enhanced nonparametric EWMA sign control chart using sequential mechanism
TypeArticle
Issue Number11
Volume Number14
dc.accessType Abstract Only


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