Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)

10.13139/ORNLNCCS/1779073

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.

Published: 2021-04-23 16:06:33 Download Dataset

Dataset Properties

Field Value
Authors
  • 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
Project Identifier Peregrine
Dataset Type SM Specialized Mix
Subjects
  • 36 MATERIALS SCIENCE
  • 97 MATHEMATICS AND COMPUTING
Keywords
  • Powder Bed Additive Manufacturing
  • Image Segmentation
  • In-Situ Process Monitoring
  • Machine Learning
Originating Organizations Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organizations 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)
DOE Contract DE-AC05-00OR22725
Related Identifiers
  • IsSupplementedBy (DOI) 10.1016/j.addma.2020.101453

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/ORNLNCCS/1779073 is provided by the U.S. Department of Energy, project Peregrine under Contract DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.