In the present work, an optimization of the clinching tools involving extensible dies is performed to increase the clinched joints strength. The clinched joint strength is influenced by the lock parameters, which in turn depend on the clinching tool geometry. A finite element model is developed to predict the effect of the clinching tool geometry on lock parameters and recursively optimize the tool geometry. In order to reduce the number of FE simulation runs, an artificial Neural Network (ANN) model is utilized to predict the behavior of clinched joints produced with a given clinching tools configuration. The ANN is trained and validated by us- ing the results of the finite element model produced under different clinching tools configurations. Finally, an optimization tool based on a Genetic Algorithm tool was developed to demonstrate the effectiveness of the proposed approach.

Optimization of the clinching tools by means of integrated FE modeling and Artificial Intelligence Techniques

LAMBIASE, FRANCESCO;DI ILIO, Antoniomaria
2013-01-01

Abstract

In the present work, an optimization of the clinching tools involving extensible dies is performed to increase the clinched joints strength. The clinched joint strength is influenced by the lock parameters, which in turn depend on the clinching tool geometry. A finite element model is developed to predict the effect of the clinching tool geometry on lock parameters and recursively optimize the tool geometry. In order to reduce the number of FE simulation runs, an artificial Neural Network (ANN) model is utilized to predict the behavior of clinched joints produced with a given clinching tools configuration. The ANN is trained and validated by us- ing the results of the finite element model produced under different clinching tools configurations. Finally, an optimization tool based on a Genetic Algorithm tool was developed to demonstrate the effectiveness of the proposed approach.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/30215
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 61
  • ???jsp.display-item.citation.isi??? 51
social impact