RESEARCH ARTICLE

Determining casting defects in near-net shape casting aluminum parts by computed tomography

  • Jiehua LI , 1 ,
  • Bernd OBERDORFER 2 ,
  • Daniel HABE 2 ,
  • Peter SCHUMACHER 1,2
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  • 1. Institute of Casting Research, Montanuniversität Leoben, Leoben A-8700, Austria
  • 2. Austrian Foundry Research Institute, Leoben A-8700, Austria

Received date: 27 Mar 2017

Accepted date: 27 Sep 2017

Published date: 23 Jan 2018

Copyright

2018 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature

Abstract

Three types of near-net shape casting aluminum parts were investigated by computed tomography to determine casting defects and evaluate quality. The first, second, and third parts were produced by low-pressure die casting (Al-12Si-0.8Cu-0.5Fe-0.9Mg-0.7Ni-0.2Zn alloy), die casting (A356, Al-7Si-0.3Mg), and semi-solid casting (A356, Al-7Si-0.3Mg), respectively. Unlike die casting (second part), low-pressure die casting (first part) significantly reduced the formation of casting defects (i.e., porosity) due to its smooth filling and solidification under pressure. No significant casting defect was observed in the third part, and this absence of defects indicates that semi-solid casting could produce high-quality near-net shape casting aluminum parts. Moreover, casting defects were mostly distributed along the eutectic grain boundaries. This finding reveals that refinement of eutectic grains is necessary to optimize the distribution of casting defects and reduce their size. This investigation demonstrated that computed tomography is an efficient method to determine casting defects in near-net shape casting aluminum parts.

Cite this article

Jiehua LI , Bernd OBERDORFER , Daniel HABE , Peter SCHUMACHER . Determining casting defects in near-net shape casting aluminum parts by computed tomography[J]. Frontiers of Mechanical Engineering, 2018 , 13(1) : 48 -52 . DOI: 10.1007/s11465-018-0493-y

Acknowledgements

Jiehua Li acknowledges the financial support provided by the Major International (Regional) Joint Research Project (Grant No. 51420105005) and Overseas, Hong Kong, Macao Scholars Cooperative Research Fund (Grant No. 51728101) from China.
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