Abstract
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.
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