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Erschienen in: Journal of Materials Engineering and Performance 3/2022

19.10.2021

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

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

Erschienen in: Journal of Materials Engineering and Performance | Ausgabe 3/2022

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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.

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Metadaten
Titel
Statistical Analysis of Laser-Welded Blanks in Deep Drawing Process: Response Surface Modeling
verfasst von
Ahmad Aminzadeh
Noushin Nasiri
Noureddine Barka
Ali Parvizi
Karen Abrinia
Mahmoud Moradi
Sasan Sattarpanah Karganroudi
Publikationsdatum
19.10.2021
Verlag
Springer US
Erschienen in
Journal of Materials Engineering and Performance / Ausgabe 3/2022
Print ISSN: 1059-9495
Elektronische ISSN: 1544-1024
DOI
https://doi.org/10.1007/s11665-021-06312-z

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