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Tytuł artykułu

Quality analysis of the Al-Si-Cu alloy castings

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The developed design methodologies both the material and technological ones will make it possible to improve shortly the quality of materials from the light alloys in the technological process, and the automatic process flow correction will make the production cost reduction possible, and - first of all - to reduce the amount of the waste products. Method was developed for analysis of the casting defects images obtained with the X-ray detector analysis of the elements made from the Al-Si-Cu alloys of the AC-AlSi7Cu3Mg type as well as the method for classification of casting defects using the artificial intelligence tools, including the neural networks; the developed method was implemented as software programs for quality control. Castings were analysed in the paper of car engine blocks and heads from the Al-Si-Cu alloys of the AC-AlSi7Cu3Mg type fabricated with the "Cosworth" technological process. The computer system, in which the artificial neural networks as well as the automatic image analysis methods were used makes automatic classification possible of defects occurring in castings from the Al-Si-Cu alloys, assisting and automating in this way the decisions about rejection of castings which do not meet the defined quality requirements, and therefore ensuring simultaneously the repeatability and objectivity of assessment of the metallurgical quality of these alloys.
Rocznik
Strony
91--94
Opis fizyczny
Bibliogr. 15 poz., rys., tab.
Twórcy
autor
  • Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, Konarskiego St. 18a, 44-100 Gliwice, leszek.dobrzanski@polsl.pl
Bibliografia
  • [1] J.P. Anson, J.E. Gruzleski: The quantitative discrimination between shrinkage and gas microporosity in cast aluminum alloys using spatial data analysis, Materials Characterization 43, (1999), Elsevier Science Inc. pp. 319-335.
  • [2] L.A. Dobrzański, R. Maniara, J.H. Sokolowski: The effect of cast Al-Si-Cu alloy solidification rate on alloy thermal characteristics, Journal of Achievements in Materials and Manufacturing Engineering, Vol. 17, Is.1-2, (2006), pp. 217-220.
  • [3] K.W. Dolan: Design and Produkt Optimization for Cast Ligot Metals, Livermore, 2000
  • [4] D. Toru, K. Soji: Development of a new aluminum alloy bearing for small-sized diesel engines, JSAE Review 21, (2000), pp. 143-147.
  • [5] Szewieczek D. Krupińska B.: Analysis of technological process on the basis of efficiency criterion, Journal of Achievements in Mechanical and Materials Engineering, Vol. 17, Is. 1-2, (2006), pp. 421-424.
  • [6] Ł. Bernat, J. Hajkowski, M. Hajkowski: Microstructure and porosity of aluminum alloy casting whereas mechanical properties, Archives of Foundry, Vol. 6, Is. 22, (2006), pp. 41-48 (in Polish).
  • [7] S. Pietrowski, R. Władysiak: Low-pressure casting process analysis of Al-Si car wheels casts, Archives of Foundry, Vol. 6, Is. 22, (2006), pp. 376-391 (in Polish).
  • [8] S. Pietrowski: Low- siliceous Al-Si alloys with Ni, Cu, and Mg additions, Archives of Foundry, Vol. 6, Is. 22, (2006), pp. 414-429 (in Polish).
  • [9] A. Shyam, Y.N. Picard, J.W. Jones, J. Allison, S.M. Yalisove: Small fatigue crack propagation from micronotches in the cast aluminum alloy W319, Scripta Materialia, Vol. 50, (2004), pp. 1109-1114.
  • [10] K.S. Chan, P. Jones, Q. Wang: Fatigue crack growth and fracture paths in sand cast B319 and A356 aluminum alloys, Materials Science and Engineering, A341, (2003), pp. 18-34.
  • [11] L. Wojnar, K.J. Kurzydłowski, J. Szala: Practice of image analysis, PTS, Kraków 2002 (in Polish).
  • [12] L.A. Dobrzański, M. Krupiński, J.H. Sokolowski: Application of artifical intelligence methods for classification of defects of Al-Si-Cu alloys castings, Archives of Foundry, Vol. 6, Is. 22, (2006), pp. 598-605 (in Polish).
  • [13] D.G. Leo Prakash, B. Prasanna, D. Regener: Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys, Computational Materials Science, Vol. 32, (2005), pp. 480-488.
  • [14] B. Krupińska, D. Szewieczek: Computer assistance in the technological process efficiency analysis, Journal of Achievements in Mechanical and Materials Engineering, Vol. 20, Is. 1-2, (2007), pp. 543-546.
  • [15] M. Krupinski, L.A. Dobrzański, J.H. Sokolowski, W. Kasprzak, G. Byczynski: Methodology for automatic control of automotive Al-Si cast components, Materials Science Forum, Vols. 539-543, (2007), pp. 339-344.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ4-0013-0019
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