PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Analysis of influence of chemical composition of Al-Si-Cu casting alloy on formation of casting defects

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: A methodology of the computer-aided determining relationship between chemical composition of aluminium alloy and castings quality was presented in the paper. Design/methodology/approach: To resolve the problem artificial neural networks were used. Classification problems were evaluated by the consideration mainly the values of mistakes and correct answers of networks for test data. On the basis of data analyzed by the neural network, which has the best quality classification of chemical composition of tested material, the concentration of alloying elements range, which have an effect on formation casting defects, were developed to eliminate them in the future. Findings: Combining of all methods making use of chemical composition of aluminium alloy and neural networks will make it possible to achieve a better casting quality. Research limitations/implications: The presented issues may be use, among others, for manufacturers of car subassemblies from light alloys, where meeting the stringent quality requirements ensures the demanded service life of the manufactured products. Originality/value: The correctly specified number of chemical composition of aluminium alloy enables such technological process control where the number of castings defects can be reduced by means of the proper correction of the process.
Rocznik
Strony
53--56
Opis fizyczny
Bibliogr. 15 poz., fot., rys.
Twórcy
autor
autor
  • Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18 a, 44-100 Gliwice, Poland, leszek.dobrzanski@polsl.pl
Bibliografia
  • [1] L.A. Dobrzański: Fundamentals of Materials Science and Physical Metallurgy. Engineering Materials with Fundamentals of Materials Design, WNT, Warszawa, 2002 (in Polish).
  • [2] L.A. Dobrzański, M. Krupiński, J.H. Sokolowski: Journal of Materials Processing Technology, 167 (2005) 456-462.
  • [3] L.A. Dobrzański, W. Sitek, M. Krupiński, J. Dobrzański: Journal of Materials Processing Technology, 157-158 (2004) 102.
  • [4] L.A. Dobrzański, W. Kasprzak, J.H. Sokołowski, R. Maniara, M. Krupiński: 13th Scientific International Conference „Achievements in Mechanical and Materials Engineering” AMME'2005 (2005) 147-150.
  • [5] L.A. Dobrzański, J. Trzaska: Journal of Materials Processing Technology, Vol. 155-156, 2004, 1950-1955.
  • [6] L.A. Dobrzański, J. Trzaska, Materials Science Forum, Vol. 437-4, 2003, 359-362.
  • [7] K.W. Dolan: Design and Produkt Optimization for Cast Ligot Metals, Livermore, 2000.
  • [8] M. Nałęcz, Neural network, Akademicka Oficyna Wydawnicza EXIT, Warszawa 2000.
  • [9] I.J. Polmear, Light Alloys, Metallurgy of the Light Metals, Second edition, 1989.
  • [10] C.H. Caceres; M.B. Djurdjevic; T.J. Stockwell, J.H. Sokolowski, Scripta Materialia, Vol. 40, 1999, pp. 631-637.
  • [11] C.H. Caceres, J.H. Sokolowski, P. Gallo: Materials Science and Engineering A271 (1999), 53-61.
  • [12] J.P. Anson, J.E. Gruzleski: Materials Characterization 43, pp. 319-335 (1999), Elsevier Science Inc., 1999.
  • [13] S.H. Mousavi Anijdan, A. Bahrami, H.R. Hosseini Madaah, A. Shafyei: Using genetic algorithm and artificial neural network analyses to design an Al-Si casting alloy of minimum porosity, Materials and Design, 27, 2006, 605-609.
  • [14] Asim Tewari, Manish Dighe, Arun M. Gokhale: Quantitative Characterization of Spatial Arrangement of Micropores in Cast Microstructures, Elsevier, Materials Characterization 40, (1998), 119-132.
  • [15] M. Avalle, G. Belingardi, M.P. Cavatorta, R. Doglione: Casting defects and fatigue strength of a die cast aluminium alloy: a comparison between standard specimens and production components, International Journal of Fatigue 24 (2002), 1-9.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BOS3-0016-0086
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.