The possibility to obtain optimized components with a reduced weight is the main driver of space and aeronautic industries in seriously considering the metal additive manufacturing (AM) technology for production. Despite the incontrovertible advantages offered by this manufacturing technique, the material produced is usually affected by the presence of internal defects, a poor surface quality, and process-induced residual stresses. These features strongly affect the fatigue performance and reproducibility of AMed parts, limiting the adoption of deterministic criteria for fatigue assessment. A probabilistic approach is therefore needed for the analysis of critical and structural components. To this aim, a fully probabilistic finite element (FE) post-processor, ProFACE, was developed by part of the authors to assess the fatigue strength and critical locations of complex components in the presence of process-induced defects. A wide benchmark activity was supported by the European Space Agency (ESA) to test the software capabilities for the life prediction of components manufactured in AlSi10Mg by L-PBF. After tuning ProFACE parameters based on the results obtained on standard fatigue specimens, the software was used to estimate the fatigue life of the components obtaining a good description of the experimental dataset for both volumetric and surface defects. The software was then used to explore the effect of the variability of the most significant parameters affecting fatigue strength of AlSi10Mg AMed components.

获得重量更轻的优化部件的可能性是航天和航空工业认真考虑将金属增材制造 (AM) 技术用于生产的主要驱动力。尽管这种制造技术具有无可争辩的优势，但所生产的材料通常会受到内部缺陷、表面质量差和工艺引起的残余应力的影响。这些特征强烈影响 AMed 零件的疲劳性能和再现性，限制了采用确定性标准进行疲劳评估。因此，需要一种概率方法来分析关键和结构组件。为此，采用全概率有限元 (FE) 后处理器 ProFACE，由部分作者开发，用于评估复杂部件在存在工艺引起的缺陷时的疲劳强度和关键位置。欧洲航天局 (ESA) 支持一项广泛的基准测试活动，以测试 L-PBF 制造的 AlSi10Mg 组件寿命预测的软件功能。根据在标准疲劳试样上获得的结果调整 ProFACE 参数后，该软件用于估计部件的疲劳寿命，从而获得对两者的实验数据集的良好描述体积和表面缺陷。然后使用该软件来探索影响 AlSi10Mg AMed 部件疲劳强度的最重要参数的可变性的影响。