DocumentCode
1802157
Title
The application of artificial neural networks to quality control charts
Author
Kopcso, David ; Pipino, Leo ; Rybolt, William
Author_Institution
Div. of Math. & Sci., Babson Coll., Babson Park, MA, USA
fYear
1993
fDate
5-8 Jan 1993
Firstpage
616
Abstract
Reports on the development of artificial neural networks that function as alternatives to conventional quality control charts. Multilayered feedforward networks using a backpropagation learning algorithm were trained and tested. The results illustrate the feasibility of using artificial neural networks to detect out-of-tolerance conditions in a manufacturing process
Keywords
backpropagation; diagrams; feedforward neural nets; production engineering computing; quality control; artificial neural networks; backpropagation learning algorithm; manufacturing process; multilayered feedforward networks; out-of-tolerance conditions; quality control charts; training; Artificial neural networks; Control charts; Educational institutions; Manufacturing processes; Mathematics; Neural networks; Process control; Quality control; Statistics; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 1993, Proceeding of the Twenty-Sixth Hawaii International Conference on
Conference_Location
Wailea, HI
Print_ISBN
0-8186-3230-5
Type
conf
DOI
10.1109/HICSS.1993.284241
Filename
284241
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