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


Advances in Automobile Engineering

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

Abstract Share this page

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

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

Relevant Topics

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version