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Title: Linking pyrometry to porosity in additively manufactured metals

Abstract

Porosity in additively manufactured metals can reduce material strength which is generally considered undesirable. Although studies have shown relationships between process parameters and porosity, monitoring strategies for defect detection and pore formation are still needed. In this paper, instantaneous anomalous conditions are detected in-situ via pyrometry during laser powder bed fusion additive manufacturing and correlated with voids observed using post-build micro-computed tomography. Large two-color pyrometry data sets were used to estimate instantaneous temperatures, melt pool orientations and aspect ratios. Machine learning algorithms were then applied to processed pyrometry data to detect outlier images and conditions. It is shown that melt pool outliers are good predictors of voids observed post-build. With this approach, real time process monitoring can be incorporated into systems to detect defect and void formation. Alternatively, using the methodology presented here, pyrometry data can be post processed for porosity assessment.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (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:
1595013
Report Number(s):
SAND-2019-14425J
Journal ID: ISSN 2214-8604; 682624
Grant/Contract Number:  
AC04-94AL85000; NA0003525
Resource Type:
Accepted Manuscript
Journal Name:
Additive Manufacturing
Additional Journal Information:
Journal Volume: 31; Journal Issue: C; Journal ID: ISSN 2214-8604
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Laser powder bed fusion; Insitu monitoring; Pyrometry; Porosity; Data analytics

Citation Formats

Mitchell, John A., Ivanoff, Thomas A., Dagel, Daryl, Madison, Jonathan D., and Jared, Bradley. Linking pyrometry to porosity in additively manufactured metals. United States: N. p., 2019. Web. doi:10.1016/j.addma.2019.100946.
Mitchell, John A., Ivanoff, Thomas A., Dagel, Daryl, Madison, Jonathan D., & Jared, Bradley. Linking pyrometry to porosity in additively manufactured metals. United States. doi:10.1016/j.addma.2019.100946.
Mitchell, John A., Ivanoff, Thomas A., Dagel, Daryl, Madison, Jonathan D., and Jared, Bradley. Sun . "Linking pyrometry to porosity in additively manufactured metals". United States. doi:10.1016/j.addma.2019.100946.
@article{osti_1595013,
title = {Linking pyrometry to porosity in additively manufactured metals},
author = {Mitchell, John A. and Ivanoff, Thomas A. and Dagel, Daryl and Madison, Jonathan D. and Jared, Bradley},
abstractNote = {Porosity in additively manufactured metals can reduce material strength which is generally considered undesirable. Although studies have shown relationships between process parameters and porosity, monitoring strategies for defect detection and pore formation are still needed. In this paper, instantaneous anomalous conditions are detected in-situ via pyrometry during laser powder bed fusion additive manufacturing and correlated with voids observed using post-build micro-computed tomography. Large two-color pyrometry data sets were used to estimate instantaneous temperatures, melt pool orientations and aspect ratios. Machine learning algorithms were then applied to processed pyrometry data to detect outlier images and conditions. It is shown that melt pool outliers are good predictors of voids observed post-build. With this approach, real time process monitoring can be incorporated into systems to detect defect and void formation. Alternatively, using the methodology presented here, pyrometry data can be post processed for porosity assessment.},
doi = {10.1016/j.addma.2019.100946},
journal = {Additive Manufacturing},
number = C,
volume = 31,
place = {United States},
year = {2019},
month = {11}
}

Journal Article:
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This content will become publicly available on November 17, 2020
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