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2025 Peregrine in-situ monitoring and training dataset for laser powder bed fusion and binder jet printers

  • Scime, Luke | Oak Ridge National Laboratory
  • Snow, Zackary | Oak Ridge National Laboratory
  • Joslin, Chase | Oak Ridge National Laboratory
  • McDonald, Trevor | Oak Ridge National Laboratory
  • Goldsby, Desarae | Oak Ridge National Laboratory
  • Richardson, Dylan | Oak Ridge National Laboratory
  • Paquit, Vincent | Oak Ridge National Laboratory
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Overview

Description

Peregrine, a software tool developed at Oak Ridge National Laboratory (ORNL), was used to collect and analyze in-situ monitoring (ISM) data from a Concept Laser M2 (Colibrium Additive) laser powder bed fusion (L-PBF) printer and an ExOne Innovent (Desktop Metal) binder jet printer. Data for four builds (print jobs) were saved to HDF5 (high performance data) files for release. Additionally, process anomalies were annotated by the authors across 37 image stacks (i.e., print layers) and are also provided as HDF5 files.

Funding Resources

DOE Contract Number

AC05-00OR22725

Originating Research Organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization

Advanced Materials and Manufacturing Technologies Office (AMMTO)

Details

DOI

10.13139/ORNLNCCS/2588140

Release Date

September 17, 2025

Dataset

Dataset Type

SM Specialized Mix

Software

A stand-alone HDF5 file viewer or a programming language (e.g., Python) with an HDF5 library.

Acknowledgements

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

Keywords

  • machine learning,
  • Powder Bed Additive Manufacturing,
  • Machine vision