Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)
- Scime, Luke | Oak Ridge National Laboratory
- Paquit, Vincent | Oak Ridge National Laboratory
- Joslin, Chase | Oak Ridge National Laboratory
- Richardson, Dylan | Oak Ridge National Laboratory
- Goldsby, Desarae | Oak Ridge National Laboratory
- Lowe, Larry | Oak Ridge National Laboratory
Overview
Description
This dataset contains layer-wise powder bed images from three different powder bed printing technologies – laser powder bed fusion, electron beam powder bed fusion, and binder jetting. This dataset was collected and annotated using the internally-developed Peregrine software tool and is designed primarily to facilitate research into anomaly defect detection using image segmentation or similar techniques. A total of 20 layers are provided for each printing technology, with each layer of data consisting of one or more calibrated images and an annotation file containing pixel-wise ground truth labels. The ground truths were labeled by domain experts, typically printer technicians. Data in this release were collected at Oak Ridge National Laboratory between 2016 and 2020 and were compiled in March 2021.
Funding resources
DOE contract number
DE-AC05-00OR22725Originating research organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring organization
Office of Energy Efficiency and Renewable Energy (EERE);Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (EE-5A);Office of Nuclear Energy (NE)Related resources
- IsSupplementedBy (DOI): https://doi.org/10.1016/j.addma.2020.101453
Details
DOI
10.13139/ORNLNCCS/1779073Release date
April 23, 2021Dataset
Dataset type
SM Specialized MixAcknowledgements
Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:
This work was carried out [in part] at Oak Ridge National Laboratory, managed by UT-Battelle, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725.
Category
- 36 MATERIALS SCIENCE,
- 97 MATHEMATICS AND COMPUTING
Keywords
- Powder Bed Additive Manufacturing,
- Image Segmentation,
- In-Situ Process Monitoring,
- Machine Learning