Simulation Based Mold Design Optimization of a Spring Flap Casting

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Abstract:

The complex nature of metal casting process brings about a need to simulate it before undertaken in a foundry. Casting simulations provide insights on flow of molten metal within the mold, solidification sequence, nature and location of defects etc. Moreover, mold design can be optimized to minimize defects without undergoing physical trials-and-errors as previously practiced in traditional metal casting. This study is based on casting an ASTM A216 WCB steel spring flap for automotive suspension system using a simulation based optimized mold design. The initial and optimized mold designs are simulated in MAGMASoft for mold filling, solidification, stress distribution and defects prediction. The results of simulations and actual castings are found to be in good agreement. It is concluded that simulations are accurate in modeling casting process and in predicting defects followed by their minimization through mold design optimization. The use of auxiliary components in a carefully designed mold can lead to a nearly defect-free and high quality cast product.

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Solid State Phenomena (Volume 305)

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178-184

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June 2020

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© 2020 Trans Tech Publications Ltd. All Rights Reserved

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[1] Z. Sun, H. Hu, X. Chen, Q. Wang, and W. Yang, Gating System Design for a Magnesium Alloy Casting,, J. Mater. Sci. Technol., vol. 24, no. 1, p.93–95, (2008).

Google Scholar

[2] U. S. Khade and S. M. Sawant, Gating Design Modification Using 3D CAD Modeling and Casting Simulation for Imrpoving the Casting Yield,, Int. J. Adv. Mech. Eng., vol. 4, no. 7, p.813–820, (2014).

Google Scholar

[3] C. M. Choudhari, B. E. Narkhede, and S. K. Mahajan, Casting Design and Simulation of Cover Plate Using AutoCAST-X Software for Defect Minimization with Experimental Validation,, Procedia Mater. Sci., vol. 6, p.786–797, (2014).

DOI: 10.1016/j.mspro.2014.07.095

Google Scholar

[4] H. Bhatt, R. Barot, K. Bhatt, H. Beravala, and J. Shah, Design Optimization of Feeding System and Solidification Simulation for Cast Iron,, Procedia Technol., vol. 14, p.357–364, (2014).

DOI: 10.1016/j.protcy.2014.08.046

Google Scholar

[5] A. Kermanpur, Sh. Mahmoudi, and A. Hajipour, Numerical simulation of metal flow and solidification in the multi-cavity casting moulds of automotive components,, J. Mater. Process. Technol., vol. 206, no. 1–3, p.62–68, Sep. (2008).

DOI: 10.1016/j.jmatprotec.2007.12.004

Google Scholar

[6] G. Mi, X. Liu, K. Wang, and H. Fu, Application of Numerical Simulation Technique to Casting Process of Valve Block,, J. Iron Steel Res. Int., vol. 16, no. 4, p.12–17, Jul. (2009).

DOI: 10.1016/s1006-706x(09)60053-4

Google Scholar

[7] D. Y. Maeng, J. H. Lee, C. W. Won, S. S. Cho, and B. S. Chun, The effects of processing parameters on the microstructure and mechanical properties of modified B390 alloy in direct squeeze casting,, J. Mater. Process. Technol., vol. 105, no. 1–2, p.196–203, Sep. (2000).

DOI: 10.1016/s0924-0136(00)00527-6

Google Scholar

[8] A. Midea, M. Burns, M. Schneider, and I. Wagner, Advanced thermo-physical data for casting process simulation –the importance of accurate sleeve properties,, Int. Foundry Res., vol. 59, no. 1, p.34–43, (2007).

Google Scholar

[9] A. Egner-Walter and M. Kothen, Using stress simulation to tackle distortion and cracking in castings,, Metall. Sci. Tecnol., vol. 24, no. 2, (2013).

Google Scholar

[10] G. Hartmann, Material combinations in light weight casting components,, Cast. Plant Technol., vol. 4, p.32–37, (2013).

Google Scholar

[11] I. Hahn and E. Hepp, Improved ingot casting by using numerical simulation.,.

Google Scholar

[12] Feeding & Risering Guidelines for Steel Castings." Steel Founders, Society of America, (2001).

Google Scholar