Improvement on Die-Casting Efficiency and Property of Aluminum Alloy Casing.

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Die-casting process is significantly used in the industry for its high productivity and less post-machining requirement. For high pressure die-casting, it needs well-design of gating and runner system; therefore, die cavity design and technology parameter calculations are essential. In the current paper of die-casting for automobile starter motor casing, the following issues are focused: filling simulation, defect analysis, and finally the use of the Taguchi multi-quality analysis method to find the optimal parameters and factors to increase the aluminum ADC10 die-casting quality and efficiency. When the casting speed is increased, the volume shortage detects due to solidification procedure can be reduced. However, if the casting speed exceeds a permissible level, the defects of gas volume and porosity will occur. After Taguchi method analysis, the results of the optimum parameters are: for the gate area of 40mm2, group 2 of the gate location, the speed of the liquid metal at the gate 50 m/s, the temperature of molten aluminum 670° C.

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518-524

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August 2014

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. Avalle, G. Belingardi, M.P. Cavatorta, Static and fatigue strength of a die cast aluminum alloy under different feeding conditions. Presented at EUROMAT 2001, Rimini 10–14 June (2001).

Google Scholar

[2] M. Avalle, G. Belingardi, M.P. Cavatorta, R. Doglione, Casting defect and fatigue strength of a die cast aluminum alloy:a comparison between standard specimens and production components, International Journal of Fatigue 24 (2002) 1–9.

DOI: 10.1016/s0142-1123(01)00112-8

Google Scholar

[3] Changyu, S., Lixia, W. & Qian, L. 2007. Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method, Journal of Materials Processing Technology, 183: 412-418.

DOI: 10.1016/j.jmatprotec.2006.10.036

Google Scholar

[4] Guilherme Ourique Verran. 2006. Influence of injection parameters on defects formation in die casting Al12Si1. 3Cu alloy: Experimental results and numeric simulation, Journal of Materials Processing Technology, 179: 190-195.

DOI: 10.1016/j.jmatprotec.2006.03.089

Google Scholar

[5] Mousavi Anijdan, S.H., Bahrami, A., Madaah Hoseini, H.R. & Shafyei, A. 2006. Using genetic algorithm and artificial neural network analyses to design an Al–Si casting alloy of minimum porosity, Materials and Design, 27: 605-609.

DOI: 10.1016/j.matdes.2004.11.027

Google Scholar

[6] Quang-Cherng Hsu and Anh Tuan Do. 2013. Minimum porosity formation in pressure die casting by Taguchi method, Mathematical Problems in Engineering.

DOI: 10.1155/2013/920865

Google Scholar

[7] Die casting Handbook, 2th edition, NADCA, (2001).

Google Scholar

[8] Handbook Volume 15: Casting, ASM International Handbook Committee, 2008, pp.715-718, 724-726.

Google Scholar

[9] ProCAST User Manual, Version 2009, ESI Group, (2009).

Google Scholar

[10] Syrcos, G.P. 2003. Die casting process optimization using Taguchi methods, Journal of Materials Processing Technology, 135: 68-74.

DOI: 10.1016/s0924-0136(02)01036-1

Google Scholar