PSI - Issue 83

E.N.T. Isidro et al. / Procedia Structural Integrity 83 (2026) 171–178

178

4. Conclusions The study highlights the importance of refining process parameters to produce superior components that replicate the properties of conventionally produced materials. A strong correlation was found between volumetric energy density (VED) and relative density. Specimens exposed to high energy densities (60-96 J/mm³) demonstrated nearly full density, achieving a relative density of roughly 99.5%. Conversely, lower energy inputs (20-26.7 J/mm³) resulted in considerable porosity, thereby reducing relative density to roughly 80%. The chessboard strategy demonstrated superior densification compared to the stripes strategy, especially at lower VED values. Furthermore, surface roughness was notably affected by energy levels; higher VED values yielded smoother surface s (Ra≈5 -7 µm), whereas lower energies induced unstable melt pools and increased roughness due to spatter and incomplete fusion. Hardness, assessed in its as-built state, displayed a significant correlation with the volumetric energy density (VED), spanning from 350 to 380 HV under optimal energy conditions; this was consistent with the martensitic microstructure characteristic of additively manufactured maraging steels. Conversely, inadequate energy input resulted in diminished hardness, a consequence of porosity. The chessboard pattern demonstrated greater and more uniform hardness values relative to the stripes pattern, implying a more favourable thermal history. These results provide crucial insights for selecting industrial parameters, thereby facilitating the efficient fabrication of high-performance maraging steel components via selective laser melting (SLM) in their as-printed condition. References Ferreira, D. F. S., Miranda, G., Oliveira, F. J., Oliveira, J. M., 2021. Predictive models for an optimized fabrication of 18Ni300 maraging steel for moulding and tooling by Selective Laser Melting. Journal of Manufacturing Processes 70: 46-54. Kučerová, L., Burdova, K., Marková, V., Zálabský, J., Ťavodová, M., 2023. Using the design of experiments methodology to eval uate the heat treatment of additively manufactured maraging steel. Journal of Materials Research and Technology 26: 8688-8703. Maodzeka, D. K., Olakanmi, E. O., Mosalagae, M., Hagedorn-Hansen, D., Pityana, S. L., 2023. Hybrid optimisation studies on the microstructural properties and wear resistance of maraging steel 1.2709 parts produced by laser powder bed fusion. Optics & Laser Technology 159: 108914. Naboni, R., Zomparelli, A., 2023. Complex modelling automation for 3D polyhedral structures built with additive formwork manufacturing. Architecture, Structures and Construction 3(2): 235-250. Sefene, E. M., 2022. State-of-the-art of selective laser melting process: A comprehensive review. Journal of Manufacturing Systems 63: 250-274. Seydgazov, R., Mirzade, F. K., 2021. Threshold conditions for thermocapillary formation of a deep cavity in the additive process for selective laser melting of a metal powder layer. Welding International 35(7-9): 359-368. Silva, F., Bartolomeu, F., Duarte, T., Alves, J. L., Miranda, G., Neto, R., Pereira, A. B., Relvas, C., Santana, L., Terroso, M. (2023). IMPRESSÃO 3D - Tecnologias, materiais e aplicações. Porto, Quântica Editora - Conteúdos Especializados, Lda. Sing, S. L., Huang, S., Goh, G. D., Goh, G. L., Tey, C. F., Tan, J. H. K., Yeong, W. Y., 2021. Emerging metallic systems for additive manufacturing: In-situ alloying and multi-metal processing in laser powder bed fusion. Progress in Materials Science 119: 100795. Sivasubramanian, K., Murthy, A., Udayasuriyan, E., Chirania, A., Renuka, C. K. (2025). Impact of industry 4.0 and additive manufacturing on modern manufacturing processes. AIP Conference Proceedings, AIP Publishing LLC. Wischeropp, T. M. (2021). Advancement of selective laser melting by laser beam shaping, Springer. Zhu, Y., Zhao, Y., Chen, B., 2022. A study on Sc-and Zr-modified Al–Mg alloys processed by selective laser melting. Materials Science and Engineering: A 833: 142516.