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The Integration of Knowledge about the Manufacturing Process of ADI with the Use of Artificial Intelligence Methods

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The authors of this article highlight the need to integrate knowledge about the design process of products made from ADI contained in thematic publications. Integration and centralization of the results can be the basis for the planning and execution of subsequent experiments, covering areas previously unexplored. The integrated knowledge can also give rise to the production of new knowledge by discovering relationships and dependencies that are not visible in single experiments. Attempts were made to construct inference algorithms and systems based on artificial intelligence methods. This article presents the results of the use of artificial neural networks and one of the methods in the area of data mining called regression trees to develop models of the ADI manufacturing process.
Rocznik
Strony
59--64
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wykr.
Twórcy
  • AGH – University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
  • AGH – University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
autor
  • AGH – University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow
Bibliografia
  • [1] Mrzygłód, B. & Regulski, K. (2011). Model of knowledge representation about materials in the form of a relational database for CAPCAST system. Archives of Foundry Engineering. 11(3), 81-86.
  • [2] Mrzygłód, B. & Ścira, K. (2012). Module to generate rules for the knowledge base in a CAPCAST expert system. Archives of Foundry Engineering. 12(2), 167-170.
  • [3] Olejarczyk-Wożeńska, I., Adrian, A., Adrian, H. & Mrzygłód, B. (2012). Parametric representation of TTT diagrams of ADI cast iron. Archives of Metallurgy and Materials. 57(2), 613-617.
  • [4] Mrzygłód, B., Adrian, A., Regulski, K., Olejarczyk-Wożeńska, I., Kluska-Nawarecka, S. (2013). The exploitation of TTTi diagrams in the CAPCAST system. Transactions Of Foundry Research Institute. 53(4), 45-56.
  • [5] Mrzygłód, B., Kluska-Nawarecka, S., Kowalski, A. & Wilk-Kołodziejczyk, D. (2013). Application of TTT diagrams low-alloy ductile iron to assist the manufacturing process of cast iron. Transactions of Foundry Research Institute, 53(4), 85-111.
  • [6] Zahiri, S.H. & Davies C.H.J., (2003). Simultaneous prediction of austemperability and processing window for austempered ductile iron. Materials Science and Technology. 19, 1761-1770.
  • [7] Dymski, S. (1999). Formation the structure and mechanical properties of ductile cast iron during isothermal bainitic transformation. Thesis No. 95. Bydgoszcz: Publishing Department ATR. (in Polish).
  • [8] Putatunda, S.K. (2001). Development of austempered ductile iron (ADI) with simultaneous high yield strength and fracture toughness by a novel two-step austempering process. Materials Science and Engineering. A315, 70-80.
  • [9] Putatunda, S.K. (2001). Influence of austempering temperature toughness of low magnese austempered ductile iron (ADI), Materials and Manufacturing Processes. 16(2).
  • [10] Janowak, J.F. & Morton, P.A. (1984). A guide to mechanical properties possible by austempering 1,5% Ni-0,3% Mo ductile iron, AFS Transactiion. 5(92), 489-498.
  • [11] Kochański, A., Kozłowski, J., Kłębczyk, M., Perzyński, P. (2010). Modeling properties of ductile iron ADI using literature data developed using the methodology of data preparation. Polish metallurgy in years 2006-2010. Krakow: WN Akapit. (in Polish).
  • [12] Tadeusiewicz, R. (1993). Neural networks. Warszawa: AOF.
  • [13] Lula, P., Paliwoda-Pękosz, G., Tadeusiewicz, R., (2007), Artificial intelligence methods and their applications in economics and management. Krakow: Publishing University of Economics.
  • [14] Regulski, K., Rojek, G., Skóra, M., Kusiak, J. (2012). Data exploration approach in control of metal forming manufacturing chain: example of fasteners production, Metal Forming 2012: proceedings of the 14th international conference on Metal Forming: September 16–19, 2012, Krakow, Poland, ed. Jan Kusiak, Janusz Majta, Danuta Szeliga, Steel Research International; spec. ed., 1319-1322.
  • [15] Regulski, K., Szeliga, D. & Kusiak, J., (2014). Data Exploration Approach Versus Sensitivity Analysis for Optimization of Metal Forming Processes. Key Engineering Materials. 611–612, 1390-1395.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-23a6c5fb-b35d-446a-98c6-a7a8459017ae
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