Header menu link for other important links
X
Prediction and optimization of thinning in automotive sealing cover using Genetic Algorithm
Published in Oxford
2016
Volume: 3.0
   
Issue: 1.0
Pages: 63.0 - 70.0
Abstract
Deep drawing is a forming process in which a blank of sheet metal is radially drawn into a forming die by the mechanical action of a punch and converted to required shape. Deep drawing involves complex material flow conditions and force distributions. Radial drawing stresses and tangential compressive stresses are induced in flange region due to the material retention property. These compressive stresses result in wrinkling phenomenon in flange region. Normally blank holder is applied for restricting wrinkles. Tensile stresses in radial direction initiate thinning in the wall region of cup. The thinning results into cracking or fracture. The finite element method is widely applied worldwide to simulate the deep drawing process. For real-life simulations of deep drawing process an accurate numerical model, as well as an accurate description of material behavior and contact conditions, is necessary. The finite element method is a powerful tool to predict material thinning deformations before prototypes are made. The proposed innovative methodology combines two techniques for prediction and optimization of thinning in automotive sealing cover. Taguchi design of experiments and analysis of variance has been applied to analyze the influencing process parameters on Thinning. Mathematical relations have been developed to correlate input process parameters and Thinning. Optimization problem has been formulated for thinning and Genetic Algorithm has been applied for optimization. Experimental validation of results proves the applicability of newly proposed approach. The optimized component when manufactured is observed to be safe, no thinning or fracture is observed.
CONTINUE READING
Figures & Tables (8)
  • Figure-0
    Fig. 1. State of stress in deep drawing.
  • Figure-1
    Fig. 3. Sealing cover – edge displacement.
  • Figure-2
    Fig. 2. Sealing cover.
  • Figure-3
    Table 1 L9 Orthogonal array for sealing cover.
  • Figure-4
    Table 2 S/N ratios for sealing cover.
  • Figure-5
    Fig. 4. Sealing cover – thickness distribution in nine ... Expand
  • Figure-6
    Table 3 Analysis of variance.
  • Figure-7
    Fig. 7. FLD – experimental results.
Citations (2)
Publications that are citing this paper.
References (11)
Publications that are referenced by this paper.
Showing 1-5 of 11 results
About the journal
JournalData powered by TypesetJournal of Computational Design and Engineering
PublisherData powered by TypesetOxford
ISSN22884300
Open AccessNo