Investigating Statistical Correlation Between Multi-Modality In-Situ Monitoring Data for Powder Bed Fusion Additive Manufacturing

Zhuo Yang, M. Adnan, Yan Lu, Fan Tien Cheng, Haw Ching Yang, Milica Perisic, Yande Ndiaye

研究成果: Conference contribution

5 引文 斯高帕斯(Scopus)

摘要

In-situ measurements provide vast information for additive manufacturing process understanding and real-time control. Data from various monitoring techniques observe different characteristics of a build process. Fusing multi-modal in-situ monitoring data can significantly enhance process anomaly detection, part defect prediction, and build failure diagnosis, thus improving AM part quality control. This paper compares the powder bed fusion in-process observations from two types of AM in-situ monitoring, coaxial melt pool imaging, and layerwise imaging, and investigates the correlation between the two observations for a build of parts with multiple geometric features and scan patterns. All data were collected from an open architecture powder bed fusion AM testbed. Data analysis shows that both datasets exhibit significant statistical changes when new features are introduced during the build. However, further machine learning-based modeling indicates that statistical features extracted from the two data sets do not correlate very well. Discussions are provided on how the statistical analysis of the observations from the two modality monitoring system can be utilized for data fusion strategy development, especially toward improving process anomaly detection.

原文English
主出版物標題2022 IEEE 18th International Conference on Automation Science and Engineering, CASE 2022
發行者IEEE Computer Society
頁面283-290
頁數8
ISBN(電子)9781665490429
DOIs
出版狀態Published - 2022
事件18th IEEE International Conference on Automation Science and Engineering, CASE 2022 - Mexico City, Mexico
持續時間: 2022 8月 202022 8月 24

出版系列

名字IEEE International Conference on Automation Science and Engineering
2022-August
ISSN(列印)2161-8070
ISSN(電子)2161-8089

Conference

Conference18th IEEE International Conference on Automation Science and Engineering, CASE 2022
國家/地區Mexico
城市Mexico City
期間22-08-2022-08-24

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 電氣與電子工程

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