Improving the quality of die castings by using artificial neural networks for porosity defect modelling Khan, M. Imad, Nahavandi, Saeid and Frayman, Yakov 2003, Improving the quality of die castings by using artificial neural networks for porosity defect modelling, in Proceedings of the 1st International Light Metals Technology Conference 2003 : 18-20 September 2003, Brisbane, Australia, CRC for CAST Metals Manafacturing, Brisbane, Qld., pp. 243-245. Attached Files Name Description MIMEType Size Downloads frayman-improvingthequalityofdiecasting-2003.pdf Published version application/pdf 222.37KB 268 Title Improving the quality of die castings by using artificial neural networks for porosity defect modelling Author(s) Khan, M. Imad Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Frayman, Yakov Conference name International Light Metals Technology Conference (1st : 2003 : Brisbane, Australia) Conference location Brisbane, Australia Conference dates 18-20 September 2003 Title of proceedings Proceedings of the 1st International Light Metals Technology Conference 2003 : 18-20 September 2003, Brisbane, Australia Editor(s) Dahle, Arne Publication date 2003 Start page 243 End page 245 Publisher CRC for CAST Metals Manafacturing Place of publication Brisbane, Qld. Summary The aim of this work is to improve the quality of castings by minimizing defects and scrap through the analysis of the data generated by High Pressure Die Casting (HPDC) Machines using computational intelligence techniques. Casting is a complex process that is affected by the interdependence of die casting process parameters on each other such that changes in one parameter results in changes in other parameters. Computational intelligence techniques have the potential to model accurately this complex relationship. The project has the potential to generate optimal configurations for HPDC Machines and explain the relationships between die casting process parameters. Notes Reproduced with the specific permission of the copyright owner. ISBN 0975132903 9780975132906 Language eng Field of Research 091207 Metals and Alloy Materials HERDC Research category E1 Full written paper - refereed Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30009621 Document type: Conference Paper Collections: School of Engineering and Technology Open Access Collection   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 02 Dec 2008, 11:47:20 EST Wed, 08 Apr 2009, 14:13:29 EST Thu, 17 Jun 2010, 15:32:24 EST Thu, 17 Jun 2010, 15:33:02 EST Mon, 30 Aug 2010, 15:18:54 EST Fri, 17 Oct 2014, 09:08:27 EST Tue, 05 Dec 2017, 06:23:42 EST Fri, 07 Sep 2018, 13:57:16 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 815 Abstract Views, 277 File Downloads  -  Detailed Statistics Created: Tue, 14 Oct 2008, 07:00:15 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.