Multiobjective Optimization of Precision Forging Process Parameters Based on Response Surface MethodReport as inadecuate




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Advances in Materials Science and Engineering - Volume 2015 2015, Article ID 893730, 7 pages -

Research Article

Key Laboratory of Metallurgical Equipment and Control of Education Ministry, Wuhan University of Science and Technology, Wuhan, Hubei 430081, China

Chongqing Construction Industrial Group Co., Ltd., Chongqing 400054, China

Received 13 April 2015; Revised 2 August 2015; Accepted 20 August 2015

Academic Editor: Philippe Miele

Copyright © 2015 Fayuan Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In order to control the precision forging forming quality and improve the service life of die, a multiobjective optimization method for process parameters design was presented by applying Latin hypercube design method and response surface model approach. Meanwhile the deformation homogeneity and material damage of forging parts were proposed for evaluating the forming quality. The forming load of die was proposed for evaluating the service life of die. Then as a case of study, the radial precision forging for a hollow shaft with variable cross section and wall thickness was carried out. The 3D rigid-plastic finite element FE model of the hollow shaft radial precision forging was established. The multiobjective optimization forecast model was established by adopting finite element results and response surface methodology. Nondominated sorting genetic algorithm-II NSGA-II was adopted to obtain the Pareto-optimal solutions. A compromise solution was selected from the Pareto solutions by using the mapping method. In the finite element study on the forming quality of forging parts and the service life of dies by multiobjective optimization process parameters, the feasibility of the multiobjective optimization method presented by this work was verified.





Author: Fayuan Zhu, Zhaohui Wang, and Mi Lv

Source: https://www.hindawi.com/



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