Surface topography analysis in cold spray additive manufacturing

Publication date

2025-05-05T15:56:51Z

2025-05-05T15:56:51Z

2025-03-01

2025-05-05T15:56:51Z

Abstract

Additive manufacturing, and particularly the cold spray technology for additive manufacturing (CSAM), is fast becoming a key technology to produce components in an efficient and environmentally friendly manner. This method usually requires a final rectification to generate specific surface topographies. The novelty of this paper is related to the capabilities of the CSAM technique to control the surface topography of the samples. Thus, this work investigates the topography of CSAM samples and its correlation with the processing parameters. Pure Al and Ti samples were manufactured following two different deposition strategies: traditional and metal knitting. This last strategy constitutes a promising alternative for CSAM to obtain near-net-final shape components. The topography was analyzed by confocal microscopy considering the form, waviness, and roughness components. Moreover, the microstructure and mechanical properties of the samples were also investigated in order to assure reliable freestanding CSAM deposits. Results showed that the waviness was controlled by the spraying line spacing, and that the waviness and roughness profiles of the metal knitting samples presented the largest wavelengths regardless the material. The metal knitting method generated samples with higher thickness and porosity than the traditional strategy, while the mechanical properties at the local scale were not varied. The study highlights the CSAM technology potential for controlling the deposit’s surface topography

Document Type

Article


Published version

Language

English

Publisher

Elsevier Inc.

Related items

Repproducció del document publicat a: https://doi.org/https://doi.org/10.1016/j.precisioneng.2024.12.007

Precision Engineering. Journal of the International Societies for Precision Engineering and Nanotechnology, 2025, vol. 92, p. 207-218

https://doi.org/https://doi.org/10.1016/j.precisioneng.2024.12.007

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Rights

cc-by-nc-nd (c) Sirvent, Paloma et al., 2025

http://creativecommons.org/licenses/by-nc-nd/4.0/

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