Building digital twins of 3D printing machines

Journal Article · Mon Dec 19 00:00:00 EST 2016 · Scripta Materialia

DOI:https://doi.org/10.1016/j.scriptamat.2016.12.005· OSTI ID:1394527

DebRoy, T. ^[1]; Zhang, W.  ^[2]; Turner, J. ^[3]; Babu, S. S. ^[4]

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1. Pennsylvania State Univ., University Park, PA (United States)
2. The Ohio State Univ., Columbus, OH (United States)
3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
4. Univ. of Tennessee, Knoxville, TN (United States)

Geometrical conformity, microstructure and properties of additively manufactured (AM) components are affected by the desired geometry and many process variables within given machines. Building structurally sound parts with good mechanical properties by trial and error is time-consuming and expensive. Today's computationally efficient, high-fidelity models can simulate the most important factors that affect the AM products' properties, and upon validation can serve as components of digital twins of 3D printing machines. This article provides a perspective of the current status and research needs for the main building blocks of a first generation digital twin of AM from the viewpoints of researchers from several organizations.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1394527
• Journal Information: Scripta Materialia, Vol. 135, Issue C; ISSN 1359-6462
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

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42 ENGINEERING