Building blocks for a digital twin of additive manufacturing

G. L. Knapp, T. Mukherjee, J. S. Zuback, H. L. Wei, Todd Palmer, A. De, Tarasankar Debroy

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

Properties and serviceability of additively manufactured components are affected by their geometry, microstructure and defects. These important attributes are now optimized by trial and error because the essential process variables cannot currently be selected from scientific principles. A recourse is to build and rigorously validate a digital twin of the additive manufacturing process that can provide accurate predictions of the spatial and temporal variations of metallurgical parameters that affect the structure and properties of components. Key building blocks of a computationally efficient first-generation digital twin of laser-based directed energy deposition additive manufacturing utilize a transient, three-dimensional model that calculates temperature and velocity fields, cooling rates, solidification parameters and deposit geometry. The measured profiles of stainless steel 316L and Alloy 800H deposits as well as the secondary dendrite arm spacing (SDAS) and Vickers hardness measurements are used to validate the proposed digital twin. The predicted cooling rates, temperature gradients, solidification rates, SDAS and micro-hardness values are shown to be more accurate than those obtained from a commonly used heat conduction calculation. These metallurgical building blocks serve as a phenomenological framework for the development of a digital twin that will make the expanding knowledge base of additive manufacturing usable in a practical way for all scientists and engineers.

Original languageEnglish (US)
Pages (from-to)390-399
Number of pages10
JournalActa Materialia
Volume135
DOIs
StatePublished - Aug 15 2017

Fingerprint

3D printers
Dendrites (metallography)
Solidification
Deposits
Cooling
Geometry
Vickers hardness
Stainless Steel
Heat conduction
Thermal gradients
Microhardness
Stainless steel
Engineers
Defects
Microstructure
Lasers
Temperature

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Ceramics and Composites
  • Polymers and Plastics
  • Metals and Alloys

Cite this

Knapp, G. L. ; Mukherjee, T. ; Zuback, J. S. ; Wei, H. L. ; Palmer, Todd ; De, A. ; Debroy, Tarasankar. / Building blocks for a digital twin of additive manufacturing. In: Acta Materialia. 2017 ; Vol. 135. pp. 390-399.
@article{81de381156f642868aa1ae0e37541017,
title = "Building blocks for a digital twin of additive manufacturing",
abstract = "Properties and serviceability of additively manufactured components are affected by their geometry, microstructure and defects. These important attributes are now optimized by trial and error because the essential process variables cannot currently be selected from scientific principles. A recourse is to build and rigorously validate a digital twin of the additive manufacturing process that can provide accurate predictions of the spatial and temporal variations of metallurgical parameters that affect the structure and properties of components. Key building blocks of a computationally efficient first-generation digital twin of laser-based directed energy deposition additive manufacturing utilize a transient, three-dimensional model that calculates temperature and velocity fields, cooling rates, solidification parameters and deposit geometry. The measured profiles of stainless steel 316L and Alloy 800H deposits as well as the secondary dendrite arm spacing (SDAS) and Vickers hardness measurements are used to validate the proposed digital twin. The predicted cooling rates, temperature gradients, solidification rates, SDAS and micro-hardness values are shown to be more accurate than those obtained from a commonly used heat conduction calculation. These metallurgical building blocks serve as a phenomenological framework for the development of a digital twin that will make the expanding knowledge base of additive manufacturing usable in a practical way for all scientists and engineers.",
author = "Knapp, {G. L.} and T. Mukherjee and Zuback, {J. S.} and Wei, {H. L.} and Todd Palmer and A. De and Tarasankar Debroy",
year = "2017",
month = "8",
day = "15",
doi = "10.1016/j.actamat.2017.06.039",
language = "English (US)",
volume = "135",
pages = "390--399",
journal = "Acta Materialia",
issn = "1359-6454",
publisher = "Elsevier Limited",

}

Building blocks for a digital twin of additive manufacturing. / Knapp, G. L.; Mukherjee, T.; Zuback, J. S.; Wei, H. L.; Palmer, Todd; De, A.; Debroy, Tarasankar.

In: Acta Materialia, Vol. 135, 15.08.2017, p. 390-399.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Building blocks for a digital twin of additive manufacturing

AU - Knapp, G. L.

AU - Mukherjee, T.

AU - Zuback, J. S.

AU - Wei, H. L.

AU - Palmer, Todd

AU - De, A.

AU - Debroy, Tarasankar

PY - 2017/8/15

Y1 - 2017/8/15

N2 - Properties and serviceability of additively manufactured components are affected by their geometry, microstructure and defects. These important attributes are now optimized by trial and error because the essential process variables cannot currently be selected from scientific principles. A recourse is to build and rigorously validate a digital twin of the additive manufacturing process that can provide accurate predictions of the spatial and temporal variations of metallurgical parameters that affect the structure and properties of components. Key building blocks of a computationally efficient first-generation digital twin of laser-based directed energy deposition additive manufacturing utilize a transient, three-dimensional model that calculates temperature and velocity fields, cooling rates, solidification parameters and deposit geometry. The measured profiles of stainless steel 316L and Alloy 800H deposits as well as the secondary dendrite arm spacing (SDAS) and Vickers hardness measurements are used to validate the proposed digital twin. The predicted cooling rates, temperature gradients, solidification rates, SDAS and micro-hardness values are shown to be more accurate than those obtained from a commonly used heat conduction calculation. These metallurgical building blocks serve as a phenomenological framework for the development of a digital twin that will make the expanding knowledge base of additive manufacturing usable in a practical way for all scientists and engineers.

AB - Properties and serviceability of additively manufactured components are affected by their geometry, microstructure and defects. These important attributes are now optimized by trial and error because the essential process variables cannot currently be selected from scientific principles. A recourse is to build and rigorously validate a digital twin of the additive manufacturing process that can provide accurate predictions of the spatial and temporal variations of metallurgical parameters that affect the structure and properties of components. Key building blocks of a computationally efficient first-generation digital twin of laser-based directed energy deposition additive manufacturing utilize a transient, three-dimensional model that calculates temperature and velocity fields, cooling rates, solidification parameters and deposit geometry. The measured profiles of stainless steel 316L and Alloy 800H deposits as well as the secondary dendrite arm spacing (SDAS) and Vickers hardness measurements are used to validate the proposed digital twin. The predicted cooling rates, temperature gradients, solidification rates, SDAS and micro-hardness values are shown to be more accurate than those obtained from a commonly used heat conduction calculation. These metallurgical building blocks serve as a phenomenological framework for the development of a digital twin that will make the expanding knowledge base of additive manufacturing usable in a practical way for all scientists and engineers.

UR - http://www.scopus.com/inward/record.url?scp=85021415524&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021415524&partnerID=8YFLogxK

U2 - 10.1016/j.actamat.2017.06.039

DO - 10.1016/j.actamat.2017.06.039

M3 - Article

AN - SCOPUS:85021415524

VL - 135

SP - 390

EP - 399

JO - Acta Materialia

JF - Acta Materialia

SN - 1359-6454

ER -