Layer-wise anomaly detection and classification for powder bed additive manufacturing processes: A machine-agnostic algorithm for real-time pixel-wise semantic segmentation
Journal Article
·
· Additive Manufacturing
Not Available
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE Office of Nuclear Energy (NE)
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1638745
- Journal Information:
- Additive Manufacturing, Journal Name: Additive Manufacturing Journal Issue: C Vol. 36; ISSN 2214-8604
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- Netherlands
- Language:
- English
Economics of additive manufacturing for end-usable metal parts
|
journal | February 2012 |
ImageNet Large Scale Visual Recognition Challenge
|
journal | April 2015 |
Laser powder-bed fusion additive manufacturing: Physics of complex melt flow and formation mechanisms of pores, spatter, and denudation zones
|
journal | April 2016 |
Deep learning
|
journal | May 2015 |
Similar Records
Federated learning-based semantic segmentation for pixel-wise defect detection in additive manufacturing
Systems and methods for powder bed additive manufacturing anomaly detection
Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)
Journal Article
·
2022
· Journal of Manufacturing Systems
·
OSTI ID:1875195
Systems and methods for powder bed additive manufacturing anomaly detection
Patent
·
2022
·
OSTI ID:1986640
+5 more
Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)
Dataset
·
2023
·
OSTI ID:1779073
+3 more