Performance of Synthetic Double Sampling Chart with Estimated Parameters Based on Expected Average Run Length
Author
Source
Journal of Probability and Statistics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-31
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
A synthetic double sampling (SDS) chart is commonly evaluated based on the assumption that process parameters (namely, mean and standard deviation) are known.
However, the process parameters are usually unknown and must be estimated from an in-control Phase-I dataset.
This will lead to deterioration in the performance of a control chart.
The average run length (ARL) has been implemented as the common performance measure in process monitoring of the SDS chart.
Computation of ARL requires practitioners to determine shift size in advance.
However, this requirement is too restricted as practitioners may not have the experience to specify the shift size in advance.
Thus, the expected average run length (EARL) is introduced to assess the performance of the SDS chart when the shift size is random.
In this paper, the SDS chart, with known and estimated process parameters, was evaluated based on EARL and compared with the performance measure, ARL.
American Psychological Association (APA)
You, Huay Woon. 2018. Performance of Synthetic Double Sampling Chart with Estimated Parameters Based on Expected Average Run Length. Journal of Probability and Statistics،Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1197698
Modern Language Association (MLA)
You, Huay Woon. Performance of Synthetic Double Sampling Chart with Estimated Parameters Based on Expected Average Run Length. Journal of Probability and Statistics No. 2018 (2018), pp.1-6.
https://search.emarefa.net/detail/BIM-1197698
American Medical Association (AMA)
You, Huay Woon. Performance of Synthetic Double Sampling Chart with Estimated Parameters Based on Expected Average Run Length. Journal of Probability and Statistics. 2018. Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1197698
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197698