Performance of new nonparametric Tukey modified exponentially weighted moving average—Moving average control chart
Khanittha Talordphop,
Saowanit Sukparungsee and
Yupaporn Areepong
PLOS ONE, 2022, vol. 17, issue 9, 1-16
Abstract:
Control charts are an amazing and essential statistical process control (SPC) instrument that is commonly used in monitoring systems to detect a specific defect in the procedure. The mixed Tukey modified exponentially weighted moving average - moving average control chart (MMEM-TCC) with motivation detection ability for fewer shifts in the process mean under symmetric and non-symmetric distributions is proposed in this paper. Average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) were used as efficiency criteria in the Monte Carlo simulation, and their efficiency was compared to existing control charts. Furthermore, the expected ARL (EARL) is a method for evaluating the performance of control charts beyond a specific range of shift sizes. The distinguishing feature of the proposed chart is that it performs efficiently in detecting small to moderate shifts. There are applications for PM 2.5 and PM 10 data that demonstrate the performance of the proposed chart.
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0275260 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 75260&type=printable (application/pdf)
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:plo:pone00:0275260
DOI: 10.1371/journal.pone.0275260
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().