标题： 揭示激光粉末床熔融中的加工-性能关系：机器学习与高通量实验的协同作用 显示英文标题

标题： Unveiling Processing--Property Relationships in Laser Powder Bed Fusion: The Synergy of Machine Learning and High-throughput Experiments

摘要： 在增材制造中实现所需的机械性能需要大量的实验，而一个明确的设计框架变得至关重要，它能够减少试验次数并节省资源。 在这里，我们提出了一种方法，融合高通量（HT）实验与分层机器学习（ML），以揭示激光粉末床熔融（LPBF）工艺参数集与选定的机械性能（抗拉强度和延展性）之间的复杂关系。 高通量方法设想了小型样品的制造，用于快速自动化的硬度和孔隙率表征，以及更少量的拉伸试样，用于更耗时的屈服强度和延展性的直接测量。 机器学习方法基于高斯过程（GPs）的顺序应用，其中首先学习工艺参数与硬度/孔隙率之间的相关性，随后由这些高斯过程采用，以关联强度和延展性与工艺参数。 最后，设计了一种优化方案，利用这些高斯过程来识别最大化强度和延展性组合的加工参数。 通过基于更大且易于收集的数据以及更小但劳动密集型的数据进行学习，我们减少了对昂贵表征的依赖，并能够探索广泛的加工空间。 我们的方法与材料无关，此处我们展示了其在17-4PH不锈钢上的应用。 显示英文摘要

摘要： Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the synergy between high-throughput (HT) experimentation and hierarchical machine learning (ML) to unveil the complex relationships between a large set of process parameters in Laser Powder Bed Fusion (LPBF) and selected mechanical properties (tensile strength and ductility). The HT method envisions the fabrication of small samples for rapid automated hardness and porosity characterization, and a smaller set of tensile specimens for more labor-intensive direct measurement of yield strength and ductility. The ML approach is based on a sequential application of Gaussian processes (GPs) where the correlations between process parameters and hardness/porosity are first learnt and subsequently adopted by the GPs that relate strength and ductility to process parameters. Finally, an optimization scheme is devised that leverages these GPs to identify the processing parameters that maximize combinations of strength and ductility. By founding the learning on larger easy-to-collect and smaller labor-intensive data, we reduce the reliance on expensive characterization and enable exploration of a large processing space. Our approach is material-agnostic and herein we demonstrate its application on 17-4PH stainless steel.