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Multi-objective optimization and sensitivity analysis of tube hydroforming

  • Honggang AnEmail author
  • Daniel E. Green
  • Jennifer Johrendt
ORIGINAL ARTICLE

Abstract

Tube hydroforming is a manufacturing process used to produce structural components in cars and trucks, and the success of this process largely depends on the careful control of parameters such as internal pressure and end-feed force. The objective of this work was to establish a methodology, and demonstrate its effectiveness, to determine the optimal process parameters for a tube hydroformed in a die with a square cross section. The Taguchi method was used to establish a design of virtual hydroforming experiments, and numerical simulations were carried out with the finite element code LS-DYNA®. A sensitivity analysis was also carried out with analysis of variance. Multi-objective functions that consider necking/fracture, wrinkling, and thinning were formulated, and the response surface methodology was used with the most sensitive factors to obtain a defect-free part. An objective function, based on the final corner radius in the part, was also included in the optimization model. The forming severity of virtual hydroformed parts was evaluated using the forming limit stress diagram and the forming limit (strain) diagram. Finally, the normal-boundary intersection method and the L 2 norm were used to obtain the Pareto-optimal solution set and the optimal solution within this set, respectively. The hydroforming process for this part was also optimized using the commercial optimization software LS-OPT®, with two different single-objective algorithms. However, the optimum load path predicted with the proposed methodology was shown to achieve a smaller corner radius. The proposed optimization technique helped to define a process window that leads to a robust manufacturing process and improved part quality.

Keywords

Multi-objective optimization FLSD Taguchi method Sensitivity analysis Pareto optimization NBI Defect-free tube hydroforming 

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Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Honggang An
    • 1
    Email author
  • Daniel E. Green
    • 1
  • Jennifer Johrendt
    • 1
  1. 1.Department of Mechanical Automotive & Materials EngineeringUniversity of WindsorWindsorCanada

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