On the Probabilistic Prediction for Extreme Geometrical Defects Induced by Laser-Based Powder Bed Fusion

Research Paper Abstract: Compared to traditional subtractive manufacturing processes, powder bed fusion (PBF) shows promise for making complex metal parts with design freedom, short development time, and environmental sustainability. However, there is a consensus within the additive manufacturing (AM) community that the random geometrical defects (e.g., porosity, lack-of-fusion) produced in PBF processes pose a great challenge to fabricating load-bearing parts, particularly under dynamic loading conditions. Therefore, it is imperative to quantify defect sizes and distributions to estimate the critical, life-limiting defect size that significantly reduces fatigue life. This paper presents a comprehensive analysis of the defects induced by selective laser melting to quantify their sizes and statistical distributions. Then four cumulative distribution functions (i.e., Weibull, Gamma, Gumbel, and Lognormal CDFs) are leveraged and compared to predict the maximum defect size based on the principle of statistics of extremes. Both the peak over threshold (POT) approach and the block maxima (BM) approach are used for these predictions. The results show that the BM approach-based predictions for all CDFs to be much larger than the measured maxima while the POT approach-based predictions have less deviation. The Weibull and Gamma CDFs were best correlated to the data, measured by Pearson’s R correlation coefficient, while the Gumbel and Lognormal CDFs were also well correlated About this data: Geometrical defects from a bulk sample of SLMed SS-316L were measured using the Feret caliper diameter method. The FC diameter defect size was quantified by inscribing each defect within the smallest circle possible and using the resulting diameter as an effective defect size. The grouping or clustering effect of defects was not accounted for in the size of the defects. Only individual defects were measured to simplify this study. A total of 769 defects were collected and measured. A Keyence VR 3100 optical microscope was used for these measurements. To observe these defects, 14 sample slices of the bulk printed sample were obtained. Only the defects within and touching the border of a 5 mm x 5 mm area of the sample slices (from both sides of the sliced sample) were measured. This is because these areas corresponded to gauge sections of the sample slices., which can be used for fatigue testing. Therefore the gauge sections are the regions from which cracks are expected to propagate due to the higher stresses that arise from the reduction in specimen cross section. This means all defects outside of these regions are not as critical and are not included in the distribution. The attached files denote the sample number (1-14) and the sample side (top/bottom face) to which the data correspond.研究论文摘要： 相较于传统减材制造工艺，粉末床熔融（PBF）技术凭借设计自由度高、研发周期短与环境友好等优势，在复杂金属构件制备领域展现出巨大应用潜力。然而，增材制造（AM）领域学界已达成共识：PBF工艺过程中产生的随机几何缺陷（如孔隙率、熔合不足）会对承力构件的制备造成极大阻碍，在动态载荷工况下这一问题尤为突出。因此，亟需对缺陷尺寸与分布特征进行量化分析，以估算显著缩短疲劳寿命的临界失效缺陷尺寸。 本研究针对选区激光熔化（SLM）工艺产生的缺陷开展全面分析，对其尺寸与统计分布进行量化表征。基于极值统计原理，本研究选取威布尔、伽马、耿贝尔及对数正态四种累积分布函数（CDF），并通过对比分析实现最大缺陷尺寸的预测。本次预测同时采用超阈值峰值（POT）法与分块极大值（BM）法两种策略。结果表明，基于BM法的四种CDF预测结果均远大于实测最大缺陷尺寸，而基于POT法的预测结果与实测值偏差更小。通过皮尔逊R相关系数评估，威布尔与伽马CDF与实测数据拟合度最优，耿贝尔与对数正态CDF同样具备良好的拟合效果。 数据集说明： 本数据集针对选区激光熔化制备的316L不锈钢（SLMed SS-316L）块状试样开展几何缺陷测量，采用费雷特卡尺直径法完成表征：将每个缺陷嵌入最小外接圆，以该圆直径作为有效缺陷尺寸。本次分析未考虑缺陷的聚集与分组效应，仅对单个缺陷进行测量以简化研究。本次研究共采集并测量769处缺陷，测量设备为基恩士VR 3100光学显微镜。 为开展缺陷观测，本次研究从块状打印试样中切割得到14片试样。仅对试样切片上5mm×5mm区域内及边界上的缺陷（涵盖切片两侧区域）进行测量，原因在于该区域对应试样切片的标距段，可直接用于疲劳测试。由于试样横截面减小会导致应力升高，裂纹通常会从标距段区域萌生并扩展，因此该区域外的缺陷对疲劳性能影响较弱，未纳入本次分布分析。 附件文件标注了数据对应的试样编号（1-14）与试样侧面（上/下面）信息。