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Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-20
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The change point identification has played a vital role in process improvement for an attribute process.
This identification is able to effectively help process personnel to quickly determine the corresponding root causes and significantly improve the underlying process.
Although many studies have focused on identifying the change point of a process, a generic identification approach has not been developed.
The typical maximum likelihood estimator (MLE) approach has limitations: particularly, the known prior process distribution and mathematical difficulties.
These deficiencies are commonly encountered in practice.
Accordingly, this study proposes an artificial neural network (ANN) mechanism to overcome the difficulties of typical MLE approach in determining the change point of an attribute process.
Specifically, the performance among the statistical process control (SPC) chart alone, the typical MLE approach, and the proposed ANN mechanism are investigated for the following cases: (1) a known attribute process distribution with the associated MLE being available to be used, (2) an unknown attribute process distribution with the MLE being unable to be used, and (3) an unknown attribute process distribution with the MLE being misused.
The superior results and the performance of the proposed approach are reported and discussed.
American Psychological Association (APA)
Shao, Yuehjen E.& Lin, Ke-Shan. 2015. Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach. Discrete Dynamics in Nature and Society،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1060805
Modern Language Association (MLA)
Shao, Yuehjen E.& Lin, Ke-Shan. Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach. Discrete Dynamics in Nature and Society No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1060805
American Medical Association (AMA)
Shao, Yuehjen E.& Lin, Ke-Shan. Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach. Discrete Dynamics in Nature and Society. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1060805
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1060805