Naslov
Parametric and nonparametric modelling of earing and hardness of deep drawn cups

Autori
Lela, Branimir ; Duplančić, Igor ; Bajić, Dražen

Izvornik
Materials Science and Technology (0267-0836) 25 (2009), 8; 969-975

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Deep drawing; Neural networks; AA8011A; Earing; Hardness

Sažetak
This study compares different approaches in modelling the earing phenomenon and hardness of cups in deep drawing process. The blank holder force (BHF), annealing temperature (AT) and annealing time (ANT) of blanks prior to deep drawing process have been chosen as the three influential parameters on the earing and hardness. In order to obtain mathematical models for the earing and hardness of the deep drawn cups, the methodology of artificial neural networks (ANNs) have been used. Bayesian network (BN), radial basis function network (RBFN), Gaussian processes (GP) and multilayer perceptron (MLP) are four different ANN approaches that have been used for the modelling. The research has been conducted on a cold-rolled Al-Fe-Si (AA8011A) aluminium sheet. After obtaining the mathematical models describing the influence of BHF and annealing on hardness and earing, a comparison of the proposed models has been performed. A search for the optimal parameters of deep drawing process has been carried out too.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

POVEZANOST RADA