DocumentCode
538668
Title
Adaptively Pattern Recognition in Statistical Process Control Using Fuzzy ART Neural Network
Author
Wang, Min ; Zan, Tao
Author_Institution
Key Lab. of Adv. Manuf. Technol., Beijing Univ. of Technol., Beijing, China
Volume
1
fYear
2010
fDate
18-20 Dec. 2010
Firstpage
160
Lastpage
163
Abstract
This paper presents a statistical Process Control (SPC) method based on Fuzzy ART (adaptive Resonance Theory) neural network. The Fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms. It is shown that the Fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms.
Keywords
fuzzy neural nets; manufacturing processes; pattern recognition; process control; statistical analysis; fuzzy art neural network; histograms; manufacturing processes; pattern recognition; statistical process control; fuzzy ART; histogram; pattern recognition; statistical process control;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2010 International Conference on
Conference_Location
ChangSha
Print_ISBN
978-0-7695-4286-7
Type
conf
DOI
10.1109/ICDMA.2010.263
Filename
5701122
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