Application of Artificial Neural Networks in the Analysis of Mechanisms Destroying Forging Tools

• Autorzy: Hawryluk M. , Mrzygłód B. , Gronostajski Z. , Głowacki M. , Olejarczyk-Wożeńska I.

Identyfikatory

DOI

10.24425/amm.2019.131114

• Języki publikacji: EN

Abstrakty

EN

This article discusses the results of studies using the developed artificial neural networks in the analysis of the occurrence of the four main mechanisms destroying the selected forging tools subjected to five different surface treatment variants (nitrided layer, pad welded layer and three hybrid layers, i.e. AlCrTiSiN, Cr/CrN and Cr/AlCrTiN). Knowledge of the forging tool durability, needed in the process of artificial neural network training, was included in the set of training data (about 800 records) derived from long-term comprehensive research carried out under industrial conditions. Based on this set, neural networks with different architectures were developed and the results concerning the intensity of the occurrence of thermal-mechanical fatigue, abrasive wear, mechanical fatigue and plastic deformation were generated for each type of the applied treatment relative to the number of forgings, pressure, friction path and temperature.

Słowa kluczowe

EN

decision support system; durability of forging tools; artificial neural network; loss of material; wear

• Wydawca: Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences
• Czasopismo: Archives of Metallurgy and Materials
• Rocznik: 2020
• Tom: Vol. 65, iss. 1
• Strony: 193--200
• Opis fizyczny: Bibliogr. 13 poz., fot., rys.

Twórcy

autor

Hawryluk M.

• Wrocław University of Science and Technology, 5 Łukasiewicza Str., 50-371 Wrocław, Poland

autor

Mrzygłód B.

• AGH University of Science and Technology, Department of Applied Computer Science and Modelling, Al. Mickiewicza 30, 30-059 Kraków, Poland

autor

Gronostajski Z.

• Wrocław University of Science and Technology, 5 Łukasiewicza Str., 50-371 Wrocław, Poland

autor

Głowacki M.

• AGH University of Science and Technology, Department of Applied Computer Science and Modelling, Al. Mickiewicza 30, 30-059 Kraków, Poland

autor

Olejarczyk-Wożeńska I.

• AGH University of Science and Technology, Department of Applied Computer Science and Modelling, Al. Mickiewicza 30, 30-059 Kraków, Poland

Bibliografia

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Uwagi

EN

1. The work was realized as a part of fundamental research financed by the Ministry of Science and Higher Education, grant no. 16.16.110.663

PL

2. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).