Heterogeneous sensor data fusion for multiscale, shape agnostic flaw detection in laser powder bed fusion additive manufacturing

Heterogeneous sensor data fusion for multiscale, shape agnostic flaw detection in laser powder bed fusion additive manufacturing

We developed and applied a novel approach for shape agnostic detection of multiscale flaws in laser powder bed fusion (LPBF) additive manufacturing using heterogenous in-situ sensor data. Flaws in LPBF range from porosity at the micro-scale (< 100 µm), layer related inconsistencies at the meso-sc...

Full description

Bibliographic Details
Main Authors: Benjamin Bevans, Christopher Barrett, Thomas Spears, Aniruddha Gaikwad, Alex Riensche, Ziyad Smoqi, Harold (Scott) Halliday, Prahalada Rao
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Virtual and Physical Prototyping
Subjects:
additive manufacturing
sensor data fusion
thermal imaging
spatter monitoring
shape agnostic monitoring
porosity
Online Access:http://dx.doi.org/10.1080/17452759.2023.2196266

Internet

http://dx.doi.org/10.1080/17452759.2023.2196266

Similar Items