SPRING BACK PREDICTION IN V-DIE BENDING PROCESS USING ARTIFICIAL NEURAL NETWORK (ANN) | ||
| Al-Qadisiyah Journal for Engineering Sciences | ||
| Article 1, Volume 10, Issue 2, June 2017, Pages 180-190 PDF (0 K) | ||
| Author | ||
| Mostafa Adel Abdullah | ||
| Abstract | ||
| The Bending process is the critical operation in the sheet forming, there are large parameters influence on operation. Spring back is considering large influential indication to specify the quality of product parts. The basic parameters which are takes to study in this paper are: speed of punch, time of hold and thickness of plate. Experiment use L16 array with four levels for every parameters using V-bending die with 900, with different thickness of (0.5,1,1.5,2) mm ,hold time (0,5,10,15) min and punch speed(10,20,50,100)mm/min, for (1050) Al –alloy having employed as the work pieces. Spring back value prediction use Artificial Neural Network with conventional configuration. The results show that the thickness of plate is the large influential parameter effect in spring back by 77.29%, then punch speed by 10.51% and hold time by 3.36%. The predict result using Artificial Neural Network shown a best accuracy with (99.35%) in spring back compared to the measured value. | ||
| Keywords | ||
| Spring Back; Bending process; artificial neural network; Prediction | ||
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