Statistical Analysis of Laser-Welded Blanks in Deep Drawing Process: Response Surface Modeling

Ahmad Aminzadeh, Noushin Nasiri, Noureddine Barka, Ali Parvizi, Karen Abrinia, Mahmoud Moradi, Sasan Sattarpanah Karganroudi

Research output: Contribution to JournalArticlepeer-review

Abstract

Nowadays, laser-welded blanks (LWBs) are an advanced approach for automobile companies to reduce the weight of their products using sheets with different thicknesses, materials, strengths, and coatings, joined by different welding methods. In this current study, experimental and numerical approaches are used to tune the parameter effects and optimize the objective. Here, a 400 W Nd: YAG laser welding machine with a pulse frequency, pulse duration, and pulse energy are set at 20 Hz, 7ms, and 11 J, respectively. Also, pure argon gas with a 20 L/min flow rate was employed for shielding. Five key process parameters such as blank holder force (50000-150000N), friction coefficient (0.1-0.2), weld speed (7.4mm/s-0.75), weld power (100-300 W), material type (ST-14, ST-44 and TPP), and sheet thickness 1 mm, are considered as process parameters. The maximum drawing depth, energy absorption, and minimum weld line displacement are conducted as objective functions. Based on the response surface method (RSM), the optimal weld parameters to produce a cup with higher drawing depth, lower weld line displacement, and higher energy absorption capacity are set at a BHF of 150,000 N, µ of 0.2, weld speed of 10.23 mm/s, and weld power of 100.17 W.
Original languageEnglish
Pages (from-to)2240-2256
Number of pages17
JournalJournal of Materials Engineering and Performance
Volume31
Early online date19 Oct 2021
DOIs
Publication statusPublished - Mar 2022

Keywords

  • ANOVA
  • deep drawing process
  • laser welding
  • laser-welded blanks
  • optimization
  • response surface method
  • RSM
  • LWBs

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