GAAA-Based Layout Method of Locating Points for Aero Thin-Walled Structure Automated Riveting

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Abstract:

Aero Thin-Walled Structure (ATWS) is tending to deformed in automated riveting. Fixture plays an important role in enhancing riveting quality of the ATWS assembly process, and an appropriate layout of locating points can decrease the assembly variation substantially. This paper focused on the layout of locating points for ATWS automated riveting, using Genetic Algorithm and Ants Algorithm (GAAA) to minimize the locating points to decrease riveting variation. Firstly, the scheme of locating points is analyzed, and all potential locating points are represented by leveled matrixes. Secondly, on base of the locating point scheme, information of potential locating points is coded as gene, and the configuration of splint is defined as chromosome; the fitness is also defined according to the Key Characteristic Points (KCPs)’ riveting variation. Thirdly, the genetic and ants manipulations are discussed individually, and the two parts are connected by threshold value of the probability for chromosome in the genetic manipulation. Lastly, a case of aircraft wing panel is studied, and the finite element analysis result proves that the purposed optimizing method can solve the layout of locating point for ATWS automated riveting well.

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Periodical:

Advanced Materials Research (Volumes 433-440)

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489-496

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January 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] N. Jayaweera, P. Webb. Automated assembly of fuselage skin panels. Assembly Automation, 2007, 27 (4), p.343–355.

DOI: 10.1108/01445150710827122

Google Scholar

[2] S. C. Cheraghi, K. Krishnan, B. Bajracharya. Effect of Variations in the Riveting Process on the Quality of Riveted Joints. International Journal of Advanced Manufacturing Technology, 2008, 39 (11-12), pp.1144-1155.

DOI: 10.1007/s00170-008-1593-3

Google Scholar

[3] X.S. Qin, W. D. Wang, A. L. Lou, T. Wei, Three-point Bracket Regulation Algorithm for Drilling and Riveting of Aerofoil. Acta Aeronautica et Astronautica Sinica 2007, 28, pp.1455-1460.

Google Scholar

[4] W. Cai, J. S. Hu, J.X. Yuan, Deformable sheet panel fixturing: principles algorithms and simulations, Journal of Manufacturing Science and Engineering 1996, 118, p.318–324.

DOI: 10.1115/1.2831031

Google Scholar

[5] B. Li, B.W. Shui K.J. Lau. Fixture configuration design for sheet metal assembly with laser welding: a case study. The International Journal of Advanced Manufacturing Technology, 2002, 19 (7), pp.501-509.

DOI: 10.1007/s001700200053

Google Scholar

[6] B. Li, H. Tang, X.P. Yang, H. Wang, Quality design of fixture planning for sheet metal assembly. The International Journal of Advanced Manufacturing Technology, 2007, 32 (7-8), pp.690-697.

DOI: 10.1007/s00170-005-0385-2

Google Scholar

[7] J. A. Camelio, S. J. Hu, D. Ceglarek. Impact of fixture design on sheet metal assembly variation. Journal of Manufacturing Systems, 2004, 23(3), pp.182-193.

DOI: 10.1016/s0278-6125(05)00006-3

Google Scholar

[8] Y. G. Liao. Optimal design of weld pattern in sheet metal assembly based on a genetic algorithm. The International Journal of Advanced Manufacturing Technology, 2005, 26(5-6) pp.512-516.

DOI: 10.1007/s00170-003-2003-5

Google Scholar

[9] B. Li and B.W. Shiu. Principle and Simulation of Fixture Configuration Design for Sheet Metal Assembly with Laser Welding, Part 2: Optimal Configuration Design with Genetic Algorithm. The International Journal of Advanced Manufacturing Technology, 2001, 18(4) pp.276-284.

DOI: 10.1007/s001700170068

Google Scholar