Robotics & Machine Learning Daily News2024,Issue(Nov.12) :59-60.

Findings in Machine Learning Reported from Hacettepe University (Optimal process parameter determination in selective laser melting via machine learning-guided sequential quadratic programing)

Hacettepe大学的机器学习发现(通过机器学习引导的序列二次规划确定选择性激光熔化的最佳工艺参数)

Robotics & Machine Learning Daily News2024,Issue(Nov.12) :59-60.

Findings in Machine Learning Reported from Hacettepe University (Optimal process parameter determination in selective laser melting via machine learning-guided sequential quadratic programing)

Hacettepe大学的机器学习发现(通过机器学习引导的序列二次规划确定选择性激光熔化的最佳工艺参数)

扫码查看

摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员讨论人工智能的新发现。根据新闻报道在Hacettepe大学,NewsRx编辑的研究表明,“选择性激光熔化(SLM)是一种非常有效的方法。”广泛应用的激光功率等关键工艺参数的添加剂制造方法,扫描速度、阴影距离和激光束直径对加工质量有重要影响零件的相对密度、硬度和表面粗糙度。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in artificial intelligence. According to news reportingout of Hacettepe University by NewsRx editors, research stated, “Selective Laser Melting (SLM) is awidely used additive manufacturing method with critical processing parameters such as L aser Power,Scanning Speed, Hatch Distance, and Laser Beam Diameter, which signi ficantly impact process qualityand mechanical properties of fabricated parts li ke Relative Density, Hardness, and Surface Roughness.”

Key words

Hacettepe University/Cyborgs/Emerging Technologies/Machine Learning

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文