电焊机2026，Vol.56Issue(3)：119-126,8.DOI:10.7512/j.issn.1001-2303.2026.03.16
基于高通量实验的增材制造工艺快速筛选方法
High-Throughput R&D-Driven Additive Manufacturing Process Optimization
摘要
Abstract
Additive Manufacturing(AM)has demonstrated substantial potential in the fabrication of advanced components;however,conventional experimental workflows are often inefficient,resulting in slow process-parameter screening and high research costs.To address this limitation,this study focuses on the Laser Powder Bed Fusion(LPBF)fabrication of M350 maraging steel and establishes a new high-throughput fabrication and performance-testing framework tailored for metal AM,together with the corresponding process-optimization strategy.Using this framework,96 specimens of 32 sets of processing parameters with a Volume Energy Density(VED)range of 90.58-277.78 J/mm3 were rapidly fabricated and evaluated within 72 hours.The resulting samples exhibited a yield strength(YS)of 1215.97-1345.37 MPa,an ultimate tensile strength(UTS)of 1237.35-1447.72 MPa,and an elongation(EL)of 16.10%-28.50%.On this basis,the sample produced under the optimal process conditions(YS=1345.37 MPa,UTS=1447.72 MPa,EL=24.77%)was subjected to comprehensive microstructural characterization,including phase analysis,crystallographic texture,and dislocation-density assessment.These results further confirm the effectiveness of the high-throughput approach for process optimization and mechanical-property assurance.This work provides essential technical support for the efficient LPBF fabrication of M350 maraging steel and offers a broadly ap-plicable pathway for the accelerated development and industrial deployment of metal additive manufacturing.关键词
高通量实验/工艺参数优化/激光粉末床熔融/马氏体时效钢Key words
high-throughput testing/process optimization/laser powder bed fusion(LPBF)/martensitic stainless steel分类
矿业与冶金引用本文复制引用
吴旭东,赵毅,何勇,何戈宁,王长春,黄科..基于高通量实验的增材制造工艺快速筛选方法[J].电焊机,2026,56(3):119-126,8.基金项目
中国核能研究院核能增材制造实验室(STRFML-2022-05、K9011027001-05-FWHT-WU-20240427) （STRFML-2022-05、K9011027001-05-FWHT-WU-20240427）
四川大学联合创新基金(HG2022173) （HG2022173）
