A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks

被引:61
作者
El-Midany, T. T. [1 ]
El-Baz, M. A. [2 ]
Abd-Elwahed, M. S.
机构
[1] Mansoura Univ, Fac Engn, Prod Engn & Mech Design Dept, Mansoura, Egypt
[2] Zagazig Univ, Fac Engn, Dept Ind Engn, Zagazig, Egypt
关键词
Multivariate statistical process control; Multivariate control charts; Pattern recognition; Artificial neural networks;
D O I
10.1016/j.eswa.2009.05.092
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
This paper describes a proposed framework for multivariate process control chart recognition. The proposed methodology uses the Artificial Neural Networks (ANNs) to recognize set of subclasses of multivariate abnormal patterns. identify the responsible variable(s) oil the occurrence of abnormal pattern and classify the abnormal pattern parameters. The performance of the proposed approach has been evaluated using a real case study. The numerical and graphical results are presented which demonstrate that the approach performs effectively in control chart multivariate pattern recognition. In addition. accurately identifies and classifies the parameters of the errant variable(s). (C) 2009 Published by Elsevier Ltd
引用
收藏
页码:1035 / 1042
页数:8
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