Model for the Prediction of Deformations in the Manufacture of Thin-Walled Parts by Wire Arc Additive Manufacturing Technology

Mikel Casuso, Fernando Veiga, Alfredo Suárez, Trunal Bhujangrao, Eider Aldalur, Teresa Artaza, Jaime Amondarain, Aitzol Lamikiz

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)
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Abstract

Gas Metal Arc Welding (GMAW) is a manufacturing technology included within the differentWire Arc Additive Manufacturing alternatives. These technologies have been generating great attention among scientists in recent decades. Its main qualities that make it highly productive with a large use of material with relatively inexpensive machine solutions make it a very advantageous technology. This paper covers the application of this technology for the manufacture of thin-walled parts. A finite element model is presented for estimating the deformations in this type of parts. This paper presents a simulation model that predicts temperatures with less than 5% error and deformations of the final part that, although quantitatively has errors of 20%, qualitatively allows to know the deformation modes of the part. Knowing the part areas subject to greater deformation may allow the future adaptation of deposition strategies or redesigns for their adaptation. These models are very useful both at a scientific and industrial level since when we find ourselves with a technology oriented to Near Net Shape (NNS) manufacturing where deformations are critical for obtaining the final part in a quality regime.
Original languageEnglish
Article number678
Pages (from-to)678
Number of pages1
JournalMetals
Volume11
Issue number5
DOIs
Publication statusPublished - 21 Apr 2021

Keywords

  • Thin wall manufacturing
  • Additive manufacturing
  • Process modelling

Project and Funding Information

  • Funding Info
  • This research was funded by the vice-counseling of technology, innovation and competitiveness of the Basque Government grant agreement kk-2019/00004 (PROCODA project) and the QUALYFAM project, through the ELKARTEK 2020 (KK-2020/00042) and the ADIFIX project funded by HAZITEK 2019 and 2020 (ZL-2019/00738, ZL-2020/00073) programs and the Spanish Government CDTI-Red Cervera Programme (EXP 00123730/IDI-20191162).

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