• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.04a
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• pp.1-10
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• 2002

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1301-1306
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• 2006

Aluminum alloys are gaining increased acceptance in the automotive and electronic industeries and cold & hot forging is the most efficient method of manufacturing such mass produced parts. This study has been investigated the microstructures and mechanical properties of A6061(Al-1.2Mg-0.8Si) alloy fabricated by cold & hot forging process for development of the future compressor block. The microstructure of cold & hot forginged specimen were composed of eutectic structure aluminum solid solution and $Mg_2Si$ precipitates. The tensile strength of as-solid solution treatment A6061 alloy revealed 291.7MPa. It was fabricated that a trial future compressor cylinder block using cold & hot forging.

• 기계와재료
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• v.8 no.4 s.30
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• pp.108-117
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• 1996

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2001.10a
• /
• pp.326-339
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• 2001

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1999.06b
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• pp.133-140
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• 1999

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2000.06a
• /
• pp.57-72
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• 2000

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2001.06a
• /
• pp.39-52
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• 2001

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2001.06a
• /
• pp.139-146
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• 2001

• Proceedings of the KAIS Fall Conference
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• 2000.04a
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• pp.12-12
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• 2000

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.36-43
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• 2003

In this paper, the warm forging process sequence has been determined to manufacture the warm forged product for the precision bevel gear used as the differential gear unit of a commercial automobile. The preform shape of bevel gear influences the dimensional accuracy and stiffness of final product. So, the design parameters related preform shape such as aspect ratio and chamfer length having an influence the formability of forged product are analyzed. Then the optimal conditions of design parameters have been selected by artificial neural network (ANN). Finally, to verify the optimal preform shape, the experiments of the warm forging of the bevel gear have been executed. The proposed method can give more systematic and economically feasible means for designing preform shape in metal forming process.