摘要
由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据NewsRx记者在澳大利亚悉尼的新闻报道，研究表明：“工艺-结构-性能(PSP)关系对于制造工艺的优化至关重要，但建立这些关系通常需要耗费时间和成本的实验，特别是对于添加剂制造(AM)，因为涉及大量的工艺参数。在本研究中，以AlSi10Mg为例，我们开发了一种新的、可解释的机器学习方法，用于预测、优化和扩展激光粉末床聚变(LPBF)的过程，同时建立PSP关系。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Sydney, Australia, by NewsRx journalists, research stated, “Process -structure -property (PSP) relati onships are critical to the optimization of manufacturing processes, but establi shing these relationships typically involves time- and cost- consuming experimen ts, especially for additive manufacturing (AM) due to the large number of proces s parameters involved. In this study, we develop a novel and interpretable machi ne learning approach for predicting, optimizing, and expanding the process windo w of laser powder bed fusion (LPBF) while simultaneously establishing PSP relati onships, using AlSi10Mg as an example.”
NETL
NSTL