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A Genetic Algorithm Approach to Weld Pattern Optimization in Sheet Metal Assembly

[+] Author Affiliations
Gene Y. Liao

Wayne State University, Detroit, MI

Paper No. IMECE2003-41111, pp. 53-58; 6 pages
  • ASME 2003 International Mechanical Engineering Congress and Exposition
  • Innovations and Applied Research in Mechanical Engineering Technology
  • Washington, DC, USA, November 15–21, 2003
  • Conference Sponsors: Mechanical Engineering Education
  • ISBN: 0-7918-3722-X | eISBN: 0-7918-4663-6, 0-7918-4664-4, 0-7918-4665-2
  • Copyright © 2003 by ASME


In sheet metal assembly process, welding operation joins two or more sheet metal parts together. Since sheet metals are subject to dimensional variation resulted from manufacturing randomness, gap may be generated at each weld pair prior to welding. These gaps are forced to close during a welding operation and accordingly undesirable structural deformation results. Optimizing the welding pattern (the number and locations of weld pairs) of an assembly process was proven to significantly improve the quality of final assembly. This paper presents a Genetic Algorithm (GA)-based optimization method to automatically search for the optimal weld pattern so that the assembly deformation is minimized. Application result of a real industrial part demonstrated that the proposed algorithm effectively achieve the objective.

Copyright © 2003 by ASME



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