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Displaying 26 - 50 of 351

KNOWLEDGE EXTRACTION IN ADDITIVE MANUFACTURING A FORMAL CONCEPT ANALYSIS APPROACH

March 20, 2024
Author(s)
Zhuo Yang, Yan Lu, Yande Ndiaye, Mario Lezoche, Herve Panetto
In Additive Manufacturing (AM), it is still a major challenge to manage part quality, which is heavily influenced by feedstock materials, process settings, and in-process control. Deviations in these factors can lead to defects in the final product

MULTI-SCALE MODEL PREDICTIVE CONTROL FOR LASER POWDER BED FUSION ADDITIVE MANUFACTURING

March 20, 2024
Author(s)
Gi Suk Hong, Zhuo Yang, Yan Lu, Brandon Lane, Ho Yeung, Jaehyuk Kim
Additive manufacturing (AM) process stability is critical for ensuring part quality. Model Predictive Control (MPC) has been widely recognized as a robust technology for controlling manufacturing processes across various industries. Despite its widespread

TOWARDS REPRODUCIBLE MACHINE LEARNING-BASED PROCESS MONITORING AND QUALITY PREDICTION RESEARCH FOR ADDITIVE MANUFACTURING

March 20, 2024
Author(s)
Yan Lu, Zhuo Yang, Jiarui Xie, Mutahar Safdar, Andrei Mircea Romascanu, Hyunwoong Ko, Yaoyao Fiona Zhao
Machine learning (ML)-based monitoring systems have been extensively developed to enhance the print quality of additive manufacturing (AM). In-situ and in-process data acquired using sensors can be used to train ML models that detect process anomalies

Results of an Interlaboratory Study on the Working Curve in Vat Photopolymerization

March 18, 2024
Author(s)
Thomas Kolibaba, Jason Killgore, Benjamin Caplins, Callie Higgins, Uwe Arp, C Cameron Miller, Yuqin Zong, Dianne L. Poster
The working curve informs resin properties and print parameters for stereolithography, digital light processing, and other photopolymer additive manufacturing (PAM) technologies. First demonstrated in 1992, the working curve measurement of cure depth vs

The development of an augmented machine learning approach for the additive manufacturing of thermoelectric materials

February 28, 2024
Author(s)
Connor V. Headley, Roberto J. Herrera del Valle, Ji Ma, Prasanna Balachandran, Vijayabarathi Ponnambalam, Saniya LeBlanc, Dylan Kirsch, Joshua B. Martin
Through the integration of machine learning (ML) techniques alongside additive manufacturing (AM) experimentation, we demonstrate an iterative process to rapidly predict laser-material interactions and melt pool geometries throughout the build parameter

Phase Composition and Phase Transformation of Additively Manufactured Nickel Alloy 718 AM Bench Artifacts

February 5, 2024
Author(s)
Fan Zhang, Aaron Johnston-Peck, Lyle E. Levine, Michael Katz, Kil-Won Moon, Maureen E. Williams, Sandra W. Young, Andrew J. Allen, Olaf Borkiewicz, Jan Ilavsky
Additive Manufacturing (AM) technologies offer unprecedented design flexibility but are limited by a lack of understanding of the material microstructure formed under their extreme and transient processing conditions and its subsequent transformation

AM Bench 2022 Macroscale Tensile Challenge at Different Orientations (CHAL-AMB2022-04-MaTTO) and Summary of Predictions

January 16, 2024
Author(s)
Newell Moser, Jake Benzing, Orion Kafka, Jordan Weaver, Nicholas Derimow, Ross Rentz, Nik Hrabe
The additive manufacturing benchmarking challenge described in this work was aimed at the prediction of average stress–strain properties for tensile specimens that were excised from blocks of non-heat-treated IN625 manufactured by laser powder bed fusion

Powder Spreading Testbed for Studying the Powder Spreading Process in Powder Bed Fusion Machines

November 29, 2023
Author(s)
Justin Whiting, Eric Whitenton, Aniruddha Das, Vipin Tondare, Jason Fox, Michael McGlauflin, Alkan Donmez, Shawn P. Moylan
The spreading of powder is an integral part of powder bed fusion-based additive manufacturing technologies; however, due to the complex nature and the number of interactions between particles, studying the powder spreading process is difficult. In order to

Layered Security Guidance for Data Asset Management in Additive Manufacturing

November 23, 2023
Author(s)
Fahad Milaat, Joshua Lubell
Manufacturing industries are increasingly adopting additive manufacturing (AM) technologies to produce functional parts in critical systems. However, the inherent complexity of both AM designs and AM processes render them attractive targets for cyber

Modeling of hierarchical solidification microstructures in metal additive manufacturing: Challenges and opportunities

October 31, 2023
Author(s)
Dilip K. Banerjee, Supriyo Ghosh, Julien Zollinger, Miha Zaloznik, Christopher Newman, Raymundo Arroyave
Metal-based additive manufacturing (AM) processes often produce parts with improved properties compared to conventional manufacturing and metal working routes. However, currently, only a few alloys can be reliably additively manufactured as the vast

Enhanced strength of additively manufactured Inconel 718 by means of a simplified heat treatment strategy

October 27, 2023
Author(s)
Jake Benzing, Nicholas Derimow, Orion Kafka, Nik Hrabe, Philipp Schumacher, Don Godfrey, Chad Beamer, Priya Pathare, Jay Carroll, Ping Lu, Isaiah Trujillo, Frank DelRio
This study simplified the heat treatment route and reduced the post-processing burden for laser powder bed fusion IN718 (a nickel-based superalloy). The tailored route retained advantageous microstructures and improved tensile strength when compared to the

Polybutadiene Click Chemistry: A Rapid and Direct Method for Vat Photopolymerization

October 10, 2023
Author(s)
Levi Moore, Van Michael Saludo, Oliver Grasdal, Kayleen Smith, Thomas Kolibaba, Jason Killgore, Jacob Marcischak, Jeremy Snyder, Gregory Yandek, Kamran Ghiassi
Thiol-ene click chemistry was utilized to crosslink unmodified commercial liquid polybutadiene, and complex geometries were printed using vat photopolymerization. Polybutadiene contains reactive moieties as a result of its production process, and were used

Part Deflection Measurements of AM-Bench IN718 3D Build Artifacts

October 6, 2023
Author(s)
Maxwell Praniewicz, Jason Fox, Jared Tarr
One of the primary barriers for adoption of additive manufacturing (AM) had been the uncertainty in the performance of AM parts due to residual stresses/strains. The rapid melting and solidification which occurs during AM processes result in high residual
Displaying 26 - 50 of 351