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Title: Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing

Abstract

A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. There has been some progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. Our paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.

Authors:
 [1];  [2]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Big Metal Additive, Inc., Golden, CO (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1411599
Report Number(s):
[SAND-2017-3072J]
[Journal ID: ISSN 2053-1613; 651938]
Grant/Contract Number:  
[AC04-94AL85000; NA0003525]
Resource Type:
Accepted Manuscript
Journal Name:
Translational Materials Research
Additional Journal Information:
[ Journal Volume: 4; Journal Issue: 4]; Journal ID: ISSN 2053-1613
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; addictive manufacturing; materials characterization; testing

Citation Formats

Roach, R. A., and Gardner, S. H. Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing. United States: N. p., 2017. Web. doi:10.1088/2053-1613/aa8513.
Roach, R. A., & Gardner, S. H. Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing. United States. doi:10.1088/2053-1613/aa8513.
Roach, R. A., and Gardner, S. H. Fri . "Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing". United States. doi:10.1088/2053-1613/aa8513. https://www.osti.gov/servlets/purl/1411599.
@article{osti_1411599,
title = {Cluster 1: commercializing additive manufacturing—hurdles in materials characterization and testing},
author = {Roach, R. A. and Gardner, S. H.},
abstractNote = {A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. There has been some progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. Our paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.},
doi = {10.1088/2053-1613/aa8513},
journal = {Translational Materials Research},
number = [4],
volume = [4],
place = {United States},
year = {2017},
month = {10}
}

Journal Article:
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