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Experimental Study on the Manufacturing of Steel Inclined Walls by Directed Energy Deposition Based on Dimensional and 3D Surface Roughness Measurements


[ 1 ] Instytut Technologii Mechanicznej, Wydział Inżynierii Mechanicznej, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.9] Mechanical engineering

Year of publication


Published in


Journal year: 2022 | Journal volume: vol. 15 | Journal number: iss. 14

Article type

scientific article

Publication language


  • additive manufacturing
  • WAAM
  • GMAW
  • 3D topography
  • steel
  • inclined walls

EN Robotic-directed energy deposition has attracted the attention of the research community and industry as a process capable of producing large metallic parts. The selection of the manufacturing conditions is a critical step in improving the process efficiency and quality of the produced parts. The present work aims at analyzing the geometry and surface topography of walls built using several conditions and inclination angles, without additional supports except for the substrate. The walls were made of AWS A5.18. ER70S-6 steel using the Wire Arc Additive Manufacturing process. The study used both dimensional and 3D topography measurements to analyze the results. As findings, the travel speed played an important role in the size of the cross-section due to the heat input to the welding zone. Heat accumulation was a critical factor in the size and accuracy of the beads. Moreover, intermediate cooling provided structures with more uniform dimensions, smaller width, and higher layer growth. The inclination of the pieces influenced the width and uniformity of the beads, generating minor imperfections on the downside of the pieces because of gravity.

Date of online publication


Pages (from - to)

4994-1 - 4994-18





Article Number: 4994

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal


Impact Factor


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