DSpace at IIT Bombay >
IITB Publications >
Please use this identifier to cite or link to this item:
|Title: ||Development of an artificial neural network to predict springback in air vee bending|
|Authors: ||INAMDAR, M|
|Issue Date: ||2000|
|Publisher: ||SPRINGER LONDON LTD|
|Citation: ||INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 16(5), 376-381|
|Abstract: ||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.|
|Appears in Collections:||Article|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.