Abstract
In additive manufacturing (AM), the surface roughness of the deposited parts remains significantly higher than the admissible range for most applications. Additionally, the surface topography of AM parts exhibits waviness profiles between tracks and layers. Therefore, post-processing is indispensable to improve surface quality. Laser-aided machining and polishing can be effective surface improvement processes that can be used due to their availability as the primary energy sources in many metal AM processes. While the initial roughness and waviness of the surface of most AM parts are very high, to achieve dimensional accuracy and minimize roughness, a high input energy density is required during machining and polishing processes although such high energy density may induce process defects and escalate the phenomenon of wavelength asperities. In this paper, we propose a systematic approach to eliminate waviness and reduce surface roughness with the combination of laser-aided machining, macro-polishing, and micro-polishing processes. While machining reduces the initial waviness, low energy density during polishing can minimize this further. The average roughness (Ra = 1.11 µm) achieved in this study with optimized process parameters for both machining and polishing demonstrates a greater than 97% reduction in roughness when compared to the as-built part.
Recommended Citation
M. M. Parvez et al., "A Novel Laser-Aided Machining and Polishing Process for Additive Manufacturing Materials with Multiple Endmill Emulating Scan Patterns," Applied Sciences, vol. 11, no. 20, article no. 9428, MDPI, Oct 2021.
The definitive version is available at https://doi.org/10.3390/app11209428
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Additive manufacturing; Aluminum deposition; Direct energy deposition; Laser-aided machining; Macro-polishing; Micro-polishing
International Standard Serial Number (ISSN)
2076-3417
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2021 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Oct 2021
Comments
This research was supported by National Science Foundation Grants CMMI-1625736 and EEC 1937128.