Taguchi method and genetic algorithm neural networks analysis of forging process of bicycle chain wheel

Dyi Cheng Chen, Ci Syong You

研究成果: Conference contribution

摘要

Recent years due to the rise of awareness of environmental protection and energy conservation are attention. Which is the most representative of the bike. Many processing factors must be controlled in the bicycle chain wheel. This study employed the rigid-plastic finite element (FE) DEFORMTM 3D software to investigate the plastic deformation behavior of an aluminum alloy workpiece as it is forged for bicycle chain wheels. Factors include the temperature of the forging billet, shear friction factor, temperature of die and punch speed control all parameters. Moreover, this study used the Taguchi method and Genetic algorithm neural networks to determine the most favorable optimization parameters. Finally, our results confirmed the suitability of the proposed design, which enabled a bicycle chain wheel die to achieve perfect forging during finite element testing.

原文English
主出版物標題Innovation for Applied Science and Technology
頁面220-224
頁數5
DOIs
出版狀態Published - 2013 二月 20
事件2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012 - Kaohsiung, Taiwan
持續時間: 2012 十一月 2 → 2012 十一月 6

出版系列

名字Applied Mechanics and Materials
卷284-287
ISSN（列印）1660-9336
ISSN（電子）1662-7482

Other

Other2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012
國家Taiwan
城市Kaohsiung
期間12-11-02 → 12-11-06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    • 引用此

    Chen, D. C., & You, C. S. (2013). Taguchi method and genetic algorithm neural networks analysis of forging process of bicycle chain wheel. 於 Innovation for Applied Science and Technology (頁 220-224). (Applied Mechanics and Materials; 卷 284-287). https://doi.org/10.4028/www.scientific.net/AMM.284-287.220