This study investigates the effects of process conditions on the inherent variabilities in fused filament fabrication (FFF) of short carbon-fiber-reinforced Nylon-6 composites, where the sources of uncertainty and their adverse effects on microstructures and Young’s modulus are quantified. Microstructural characteristics such as fiber volume fraction, void volume fraction, and their spatial distributions are first extracted via image-based data analytics, and then their uncertainties are quantified by the analysis of variance. A Monte Carlo sampling method is introduced to enrich the datasets for analyzing uncertainty propagation from micro-level (microstructures) to macro-level (mechanical property). A modified Halpin-Tsai model with the consideration of fiber and void distributions is developed to quantify the propagated uncertainties on Young’s modulus, which are further validated through quasi-static tensile tests. This study examined the process-structure-property relationship of FFF samples and quantified the underlying variations in both micro- and macro-levels.

这项研究调查了工艺条件对短碳纤维增强尼龙6复合材料的熔丝制造（FFF）固有变异性的影响，其中量化了不确定性的来源及其对微结构和杨氏模量的不利影响。首先通过基于图像的数据分析提取诸如纤维体积分数，空隙体积分数及其空间分布之类的微观结构特征，然后通过方差分析对它们的不确定性进行量化。引入了蒙特卡洛采样方法，以丰富数据集，以分析从微观（微观结构）到宏观（机械特性）的不确定性传播。开发了一种考虑纤维和空隙分布的改进的Halpin-Tsai模型，以量化杨氏模量的传播不确定性，并通过准静态拉伸试验对其进行了进一步验证。这项研究检查了FFF样品的过程-结构-性质关系，并量化了微观和宏观水平的潜在变化。