Abstract
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 and annealing time of blanks before deep drawing process have been chosen as the three influential parameters on the earing and hardness. To obtain mathematical models for the earing and hardness of the deep drawn cups, the methodology of artificial neural networks have been used. Bayesian network, radial basis function network, Gaussian processes and multilayer perceptron 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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
