Szczegóły publikacji
Opis bibliograficzny
Sensitivity analysis of the artificial neural network inputs in a system to durability prediction of forging tools / MRZYGŁÓD Barbara, Hawryluk Marek, Polak Sławomir // W: Metal 2017 : 26th international conference on Metallurgy and materials : May 24th–26th 2017, Brno, Czech Republic, EU : abstracts. — Ostrava : TANGER Ltd., cop. 2017. — ISBN: 978-80-87294-73-4. — S. 110–111. — Pełny tekst na CD-ROMie. — S. 484–489. — Wymagania systemowe: Adobe Reader ; napęd CD-ROM. — Bibliogr. s. 488-489, Abstr. — ISBN 978-80-87294-79-6
Autorzy (3)
- AGHMrzygłód Barbara
- Hawryluk Marek
- Polak Sławomir
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 105978 |
|---|---|
| Data dodania do BaDAP | 2017-07-01 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | 26th International Conference on Metallurgy and Materials |
Abstract
The paper presents the results of neural network sensitivity analysis used in prediction system of tool durability in die forging processes. Data collected during many experiments, tabulated in the form of knowledge vectors, has been used as a source of training data for artificial neural networks. The sensitivity analysis makes it possible to differentiate between the important variables and those which do not make a significant contribution to the results of the network operation. The obtained results of global sensitivity analysis, conducted for the elaborated network in the context of predicting the life of forging tools from the expert viewpoint, indicate general correctness and validity of the adopted model (solution), ascribing the highest sensitivity to the nitritiding input variable (related to hardness), which is in reality the main factor determining the tool resistance to the destructive effect of failure mechanisms.