Defect Modeling During the SLM Process for Manufacturing Microwave Devices

Shuai Li*, Xiue Bao*, Giovanni Gugliandolo, Haoyun Yuan*, Jinkai Li, Linxiang Shao*, Minghe Du, Nicola Donato, Zlatica Marinkovic, Giovanni Crupi, Lili Fang*, Liming Si*, Houjun Sun*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper intends to address the issue of crack formation and other flaws during the selective laser melting (SLM) additive manufacturing process. To achieve this objective, image processing, 3D modeling, and deep-learning techniques are employed to generate a 3D defect model, while data statistics are utilized for enhancing and optimizing the entire additive manufacturing process, including adjusting manufacturing process parameters, optimizing strategies, reducing defects, and improving the yield rate of SLM. After training and adjustment, the crack recognition accuracy of the final model can reach 92.3%.

源语言英语
主期刊名2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
412-416
页数5
ISBN(电子版)9798350300802
DOI
出版状态已出版 - 2023
活动2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Milano, 意大利
期限: 25 10月 202327 10月 2023

出版系列

姓名2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Proceedings

会议

会议2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023
国家/地区意大利
Milano
时期25/10/2327/10/23

指纹

探究 'Defect Modeling During the SLM Process for Manufacturing Microwave Devices' 的科研主题。它们共同构成独一无二的指纹。

引用此