A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282

Zahabul Islam, Ankur Kumar Agrawal, Behzad Rankouhi, Collin Magnin, Mark H. Anderson, Frank E. Pfefferkorn, Dan J. Thoma

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

This paper demonstrates how an analytical and experimental method can be used to rapidly define the additive manufacturing settings for a new alloy where the process parameters were previously unknown. A nickel-based superalloy, Haynes 282, was chosen for the analysis. An experimental matrix of focused processing parameters was predicted with a dimensionless number and 100 samples were printed using the Laser Powder Bed Fusion technique. High-throughput measurements validated the predicted process conditions needed to achieve desired density and hardness. The whole process was completed in 16 hours. The new technique was confirmed with analytical processing maps adopted by the metal additive manufacturing community. With the predicted set of process parameters, a low-throughput analyses of conventional microstructural characterizations and tensile testing were used to test the predictions. The resultant as-fabricated microstructures have refined length scales of both microsegregation and secondary phase distributions. The mechanical properties were comparable within the predicted processing window and exhibited high strength and high ductility.

Original languageEnglish (US)
Pages (from-to)250-263
Number of pages14
JournalMetallurgical and Materials Transactions A: Physical Metallurgy and Materials Science
Volume53
Issue number1
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics
  • Mechanics of Materials
  • Metals and Alloys

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