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Process optimization research on surface remelting treatment of additive manufactured 316L stainless steel by circular oscillating laser Cover

Process optimization research on surface remelting treatment of additive manufactured 316L stainless steel by circular oscillating laser

Open Access
|Jul 2026

Abstract

This study adopted circular oscillating laser remelting (COLR) to postprocess additive manufactured 316L stainless steel surfaces, systematically exploring its influence on surface roughness, subsurface defects, and material properties. Extended depth-of-field microscopy and scanning electron microscopy (SEM) were employed to characterize surface and cross-sectional morphologies, revealing surface-adhered spherical particles and subsurface defects (microcracks, pores, and ablation marks) predominantly distributed at 30–50 μm depth, with maximum crack depth reaching 99.98 μm and ablation particle depth of 46.77 μm. Response surface methodology was used to investigate the effects of key parameters (laser power, scanning speed, and rotation speed) on surface roughness and remelting depth. Results showed that at 120 W, insufficient energy–induced serrated undulations and molten pools of 40–50 μm with columnar grains; at 150 W, 23.41 μm-wide and 1.00 μm-high black micro-protrusions formed, accompanied by pools of 94–136 μm with columnar-equiaxed composite grains; at 180 W, violent pool fluctuations and edge spatters occurred, producing pools of 195–239 μm with 10 μm-thick columnar grains on the outer surface of the central region. Under the optimal parameters of 180 W, 5 mm/s, and 40 % rotation speed, COLR treatment reduced the surface roughness by ∼91% (from 7.3 to 0.65 μm) and increased the average microhardness of the remelted zone from approximately 222 HV (substrate) to 249 HV.

DOI: https://doi.org/10.2478/msp-2026-0009 | Journal eISSN: 2083-134X | Journal ISSN: 2083-1331
Language: English
Page range: 138 - 163
Submitted on: Jan 26, 2026
Accepted on: May 28, 2026
Published on: Jul 10, 2026
In partnership with: Paradigm Publishing Services

© 2026 Genyi Li, Pin Li, Jianhua Shu, Xinzhong Zhang, Haoyu Wang, Zongbao Shen, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.