ISSN:
1433-3015
Keywords:
Abductive network
;
Deep-drawing
;
Die
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Abstract In this paper, the modelling of deep-drawing processing using neural networks is established. The relationships between process parameter (material thickness, punch diameter, die-cavity diameter and materials-clearance ratio) and deep-drawing performance (the dimensional error of diameter and cylinder) are created, based on a neural network. A simulated annealing (SA) optimisation algorithm with a performance index is then applied to the neural network to search for the optimal design parameters of the drawing-die. Experimental results have shown that deep-drawing performance can be enhanced by using this approach.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01304617
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