Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning
In powder bed fusion additive manufacturing, machines are often equipped with in-situ sensors to monitor the build environment as well as machine actuators and subsystems. The data from these sensors offer rich information about the consistency of the fabrication process within a build and across bu...
Guardado en:
Autores principales: | William Halsey, Derek Rose, Luke Scime, Ryan Dehoff, Vincent Paquit |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/00ef93f7d9dd4865b96ad70a73562665 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization
por: Morteza Esmaeili, et al.
Publicado: (2021) -
Turning the blackbox into a glassbox: An explainable machine learning approach for understanding hospitality customer
por: Ritu Sharma, et al.
Publicado: (2021) -
Neural Network Explainable AI Based on Paraconsistent Analysis: An Extension
por: Francisco S. Marcondes, et al.
Publicado: (2021) -
Automated Multidimensional Analysis of Global Events With Entity Detection, Sentiment Analysis and Anomaly Detection
por: Fahim K. Sufi, et al.
Publicado: (2021) -
Analysis of spatio-temporal transmission characteristicsfor H7N9 infection in China
por: Baoyun WANG, et al.
Publicado: (2021)