A Framework for Diagnosing the Out-of-Control Signals in Multivariate Process Using Optimized Support Vector Machines
Joint Authors
Li, Tai-fu
Hu, Sheng
Wei, Zheng-yuan
Liao, Zhi-qiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-02
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Multivariate statistical process control is the continuation and development of unitary statistical process control.
Most multivariate statistical quality control charts are usually used (in manufacturing and service industries) to determine whether a process is performing as intended or if there are some unnatural causes of variation upon an overall statistics.
Once the control chart detects out-of-control signals, one difficulty encountered with multivariate control charts is the interpretation of an out-of-control signal.
That is, we have to determine whether one or more or a combination of variables is responsible for the abnormal signal.
A novel approach for diagnosing the out-of-control signals in the multivariate process is described in this paper.
The proposed methodology uses the optimized support vector machines (support vector machine classification based on genetic algorithm) to recognize set of subclasses of multivariate abnormal patters, identify the responsible variable(s) on the occurrence of abnormal pattern.
Multiple sets of experiments are used to verify this model.
The performance of the proposed approach demonstrates that this model can accurately classify the source(s) of out-of-control signal and even outperforms the conventional multivariate control scheme.
American Psychological Association (APA)
Li, Tai-fu& Hu, Sheng& Wei, Zheng-yuan& Liao, Zhi-qiang. 2013. A Framework for Diagnosing the Out-of-Control Signals in Multivariate Process Using Optimized Support Vector Machines. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009580
Modern Language Association (MLA)
Li, Tai-fu…[et al.]. A Framework for Diagnosing the Out-of-Control Signals in Multivariate Process Using Optimized Support Vector Machines. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1009580
American Medical Association (AMA)
Li, Tai-fu& Hu, Sheng& Wei, Zheng-yuan& Liao, Zhi-qiang. A Framework for Diagnosing the Out-of-Control Signals in Multivariate Process Using Optimized Support Vector Machines. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009580
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009580