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Modelling of porosity defects in high pressure die casting with a neural network

Khan, Imad M., Frayman, Yakov and Nahavandi, Saeid 2003, Modelling of porosity defects in high pressure die casting with a neural network, in InTech'03 : Proceedings of the Fourth International Conference on Intelligent Technologies 2003, Chiang Mai University, Institute for Science and Technology Research and Development, Chiang Mai, Thailand, pp. 1-6.

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Title Modelling of porosity defects in high pressure die casting with a neural network
Author(s) Khan, Imad M.
Frayman, Yakov
Nahavandi, Saeid
Conference name International Conference on Intelligent Technologies (4th : 2003, Thailand)
Conference location Chiang Mai Plaza, Thailand
Conference dates 17-19 December 2003
Title of proceedings InTech'03 : Proceedings of the Fourth International Conference on Intelligent Technologies 2003
Editor(s) Dhompongsa, Sompong
Publication date 2003
Conference series International Conference on Intelligent Technologies
Start page 1
End page 6
Publisher Chiang Mai University, Institute for Science and Technology Research and Development
Place of publication Chiang Mai, Thailand
Keyword(s) artificial neural network
high pressure die casting
porosity
Summary High Pressure Die Casting (HPDC) is a complex process that results in casting defects if configured improperly. However, finding out the optimal configuration is a non-trivial task as eliminating one of the casting defects (for example, porosity) can result in occurrence of other casting defects. The industry generally tries to eliminate the defects by trial and error which is an expensive and error -prone process. This paper aims to improve current modelling and understanding of defects formation in HPDC machines. We have conducted conventional die casting tests with a neural network model of HPDC machine and compared the obtained results with the current understanding of formation of porosity. While most of our findings correspond well to established knowledge in the field, some of our findings are in conflict with the previous studies of die casting.
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ISBN 9746581511
9789746581516
Language eng
Field of Research 091499 Resources Engineering and Extractive Metallurgy not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30005259

Document type: Conference Paper
Collections: School of Engineering and Technology
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