Journal
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Volume 16, Issue 5, Pages 376-381Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s001700050169
Keywords
artificial neural network; springback; vee air bending
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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.
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