Understanding roughness parameters in ultra-thin L-PBF walls: A model-based investigation of surface defects

Surface roughness remains a major concern in laser powder bed fusion (L-PBF), particularly in the context of thin-walled components where dimensional accuracy and fatigue performance are highly sensitive to surface defects. Although track energy density (TED) is known to influence surface quality, the underlying mechanisms remain poorly understood. In this work, a simplified geometry-based model is developed to explore the contribution of melt-pool geometry and sintered powder particles to surface roughness. The model relies on idealized stacked melt-pool shapes and randomly distributed surface particles, and is calibrated using experimental observations from L-PBF samples processed at different TED values. While the arithmetic average roughness (Ra) is commonly used to assess surface quality, this study emphasizes the relevance of additional parameters – Rp, Rv, Rsk, and Rku – to better capture the morphological nature and statistical distribution of surface defects. Importantly, the results show that surface-adhered powder particles play a dominant role in shaping roughness, particularly at lower TED values. The model successfully reproduces experimental roughness trends and provides insight into the origin of surface features. These results demonstrate how different roughness parameters reflect specific surface morphologies and provide a framework for interpreting surface roughness beyond Ra in additive manufacturing.

Affiliations

UCLouvainSST/IMMC/IMAP - Materials and process engineering

Citations

APA
Chicago
FWB

Poncelet, O., van der Rest, C., & Simar, A. (2026). Understanding roughness parameters in ultra-thin L-PBF walls: A model-based investigation of surface defects. Journal of Manufacturing Processes, 168, 192-207. https://doi.org/10.1016/j.jmapro.2026.03.059 (Original work published 2026)