Finite Element Analysis and Multi-Objective Optimization of the Precision Horizontal Machining Center Bed

Article Preview

Abstract:

In order to improve dynamic and static performance of the precision horizontal machining center, the method of multi-objective optimization based on the response surface model was applied for optimizing design of the bed structure. The design variables were the layout parameters of the rib plates. Sample points were obtained by the Box-Behnken design experiment, and responses of sample points were analyzed by SAMCEF. The maximum deformation of guide rails and the low-order natural frequency were extracted to fit the response surface model by least square method. The layout parameters of the rib plates were optimized through the application of multi-objective genetic algorithms. Then, relationship between the lightening holes and the performance were analyzed to determine the suitable diameter. The results verify the validity of the optimization method, and the paper provides methodological guidance for optimization of machine tool structural parts.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 889-890)

Pages:

130-134

Citation:

Online since:

February 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Xiaoyu Ni, Hong Yi, Wencheng Tang and Zhonghua Ni. Manufacturing Technology & Machine Tool, 2 (2005): 47-50. (In Chinese).

Google Scholar

[2] Xueling Zhang, Yanshen Xu and Weihong Zhong. Journal of Mechanical Strength, 27. 3 (2005): 353-357. (In Chinese).

Google Scholar

[3] Xiaohong Ding, Yelin Chen, Wei Liu. Optimal design approach for eco-efficient machine tool bed. International Journal of Mechanics and Materials in Design, 6. 4 (2010): 351-358.

DOI: 10.1007/s10999-010-9142-2

Google Scholar

[4] Ramon Maj and Giacomo Bianchi. Mechatronic analysis of machine tools. 9th SAMTECH Users Conference, PARIS, France. (2005).

Google Scholar

[5] Nuran Bradley. The response surface methodology. Diss: Indiana University South Bend, (2007).

Google Scholar