alexa Optimization of Low-Pressure Die Casting Process with Soft Computing
Engineering

Engineering

Advances in Automobile Engineering

Author(s): Xiang Zhang, Shuiguang Tong, Li Xu

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The paper presents a hybrid strategy in a soft computing paradigm for the optimization of the low-pressure die casting process. Casting process parameters, such as various parts temperatures of die, pouring temperature are considered. The hybrid strategy combines numerical simulation software, a genetic algorithm and a multilayer neural network to optimize the process parameters. An approximate analysis model is developed using a BP neural network in order to avoid the expensive computation resulting from the numerical simulation software. According to the characteristic of the optimization problem, a real-code genetic algorithm is applied to solve the optimization model. The effectiveness of the improved strategy is shown by an A356 automotive wheel.

This article was published in IEEE xplore and referenced in Advances in Automobile Engineering

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