An Intelligent Tool to Predict Fracture in Sheet Metal Forming Operations
| Autor: | Giuseppe Ingarao, Fabrizio Micari, Rosanna Di Lorenzo |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Engineering
Artificial neural network business.industry Mechanical Engineering Mechanical engineering Neural network nn Structural engineering Early results Mechanics of Materials visual_art Fracture (geology) visual_art.visual_art_medium Formability General Materials Science business Sheet metal Production quality Necking |
| Zdroj: | Key Engineering Materials. 344:841-846 |
| ISSN: | 1662-9795 |
| DOI: | 10.4028/www.scientific.net/kem.344.841 |
| Popis: | One of the main issues in sheet metal forming operations design is the determination of formability limits in order to prevent necking and fracture. In fact, the ability to predict fracture represents a powerful tool to improve the production quality in mechanical industry. Many researchers investigated the problem here addressed, mainly studying forming limit diagrams (FLD) or developing fracture criteria which are able to foresee fracture defects for different processes. In this paper, the author present some early results of a research project focused on the application of artificial intelligence (AI) for ductile fracture prediction in sheet metal forming operations. The main advantage of the application of AI tools and in particular, of artificial neural networks (ANN), is the possibility to obtain a predictive tool with a wide applicability. The prediction results obtained in this paper fully demonstrate the usefulness of the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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