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Development of an artificial neural network to predict springback in air vee bending

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Title Development of an artificial neural network to predict springback in air vee bending
 
Creator INAMDAR, M
DATE, PP
NARASIMHAN, K
MAITI, SK
SINGH, UP
 
Subject artificial neural network
springback
vee air bending
 
Description Springback is a serious problem in the air vee bending process because of its inconsistency. An on-line tool to control springback is more reliable than an analytical model which might not be able to control the stroke of the machine in real-time. Therefore, one might resort to adaptive control or use an artificial neural network (ANN) trainer, either using experimental data or analytical predictions (or both), and use it for real-time control of the machine tool. The inconsistency in springback is then reduced to within acceptable limits. Adaptive control would need several strokes to complete the job, but it is envisaged that the job could be completed in a single stroke with the ANN. The present paper discusses the development of an ANN which can be used to train and later to predict the springback, as well as the punch travel, to achieve the desired angle in a single stroke in an air vee bending process.
 
Publisher SPRINGER LONDON LTD
 
Date 2011-08-30T06:51:48Z
2011-12-26T12:58:48Z
2011-12-27T05:49:22Z
2011-08-30T06:51:48Z
2011-12-26T12:58:48Z
2011-12-27T05:49:22Z
2000
 
Type Article
 
Identifier INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 16(5), 376-381
0268-3768
http://dx.doi.org/10.1007/s001700050169
http://dspace.library.iitb.ac.in/xmlui/handle/10054/12224
http://hdl.handle.net/10054/12224
 
Language en