Investigating Statistical Correlation Between Multiple In-Situ Monitoring Datasets for Powder Bed Fusion Additive Manufacturing

Published

August 24, 2022

Author(s)

Zhuo Yang, Yan Lu, Milica Perisic, Yande Ndiaye, Adnan Gujjar, Fan-Tien Cheng, Haw-Ching Yang

Abstract

In-situ measurements provide vast information for additive manufacturing process understanding and real-time control. Data from various monitoring techniques observes 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 improve 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 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.

Proceedings Title

Investigating Statistical Correlation Between Multiple In-Situ Monitoring Datasets for Powder Bed Fusion Additive Manufacturing

Conference Dates

August 20-24, 2022

Conference Location

Mexico City, MX

Conference Title

IEEE CASE 2022

Pub Type

Conferences

Download Paper

https://doi.org/10.1109/CASE49997.2022.9926715

Local Download

Keywords

Additive Manufacturing, Laser Powder Bed Fusion, Statistical Analysis, Machine Learning

Citation

Yang, Z. , Lu, Y. , Perišić, M. , Ndiaye, Y. , Gujjar, A. , Cheng, F. and Yang, H. (2022), Investigating Statistical Correlation Between Multiple In-Situ Monitoring Datasets for Powder Bed Fusion Additive Manufacturing, Investigating Statistical Correlation Between Multiple In-Situ Monitoring Datasets for Powder Bed Fusion Additive Manufacturing, Mexico City, MX, [online], https://doi.org/10.1109/CASE49997.2022.9926715, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934894 (Accessed October 9, 2025)