In situ characterisation of surface roughness and its amplification during multilayer single-track laser powder bed fusion additive manufacturing
In situ characterisation of surface roughness and its amplification during multilayer single-track laser powder bed fusion additive manufacturing
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DOI：
10.1016/j.addma.2023.103809
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发表时间：
2023-10
影响因子：
11
通讯作者：
Alisha Bhatt;Yuze Huang;C. L. Leung;Gowtham Soundarapandiyan;S. Marussi;Saurabh Shah;Robert C. Atwood-Robe
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文献类型：
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作者：
Alisha Bhatt;Yuze Huang;C. L. Leung;Gowtham Soundarapandiyan;S. Marussi;Saurabh Shah;Robert C. Atwood-Robe
表面粗糙度控制着激光粉床熔化(LPBF)组件的机械性能和耐用性(例如，耐磨性和耐腐蚀性)。由于缺乏表面表征方法，LPBF过程中表面粗糙度的演变机制还不是很清楚。在这里，我们利用同步辐射X射线成像和环境光学成像对关键工艺和缺陷动力学进行了量化，并解释了在Ti-6Al-4V多层LPBF过程中(底层粗糙度不在项目范围内)侧皮和顶皮粗糙度的演变机制。我们发现，仅靠平均表面粗糙度并不能准确地表示LPBF组件的表面拓扑，并且表面拓扑是多峰的(例如，包含粗糙度和波动度)和多尺度(例如，从25微米的烧结粉末特征到250微米的熔池波长)。预制层驼峰、飞溅和波纹缺陷的形成对表面粗糙度和表面形貌都有很大影响。通过综合平均粗糙度、均方根粗糙度、最大轮廓峰高、最大轮廓谷高、平均高度、平均宽度、偏斜度和熔池尺寸比8个不同的度量，我们建立了一个能够准确描述表面特征的表面拓扑矩阵。该矩阵为确定合适的线能量密度以获得最佳表面光洁度提供了指导。这项工作为表面纹理控制奠定了基础，表面纹理控制对LPBF的构建设计、计量和性能至关重要。
Surface roughness controls the mechanical performance and durability (e.g.,wear and corrosion resistance) of laser powder bed fusion (LPBF) components. The evolution mechanisms of surface roughness during LPBF are not well understood due to a lack ofin situcharacterisation methods. Here, we quantified key processes and defect dynamics using synchrotron X-ray imaging andex situoptical imaging and explained the evolution mechanisms of side-skin and top-skin roughness during multi-layer LPBF of Ti-6Al-4V (where down-skin roughness was out of the project scope). We found that the average surface roughness alone is not an accurate representation of surface topology of an LPBF component and that the surface topology is multimodal (e.g., containing both roughness and waviness) and multiscale (e.g., from 25 µm sintered powder features to 250 µm molten pool wavelength). Both roughness and topology are significantly affected by the formation of pre-layer humping, spatter, and rippling defects. We developed a surface topology matrix that accurately describes surface features by combining 8 different metrics: average roughness, root mean square roughness, maximum profile peak height, maximum profile valley height, mean height, mean width, skewness, and melt pool size ratio. This matrix provides a guide to determine the appropriate linear energy density to achieve the optimum surface finish of Ti-6Al-4V thin-wall builds. This work lays a foundation for surface texture control which is critical for build design, metrology, and performance in LPBF.