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Arash Samaei, Joseph Leonor, zhengtao gan, Zhongsheng Sang, Xiaoyu Xie, Brian Simonds, Wing Kam Liu, Gregory Wagner
Metal 3D printing involves a multitude of operational and material parameters that exhibit intricate interdependencies, which pose challenges to real-time process optimization, monitoring, and controlling. The dynamic behavior of the laser-induced melt
Thomas P. Forbes, J Greg Gillen, William Feeney, Johnny Ho
Distributed and point-of-care (POC) manufacturing facilities enable an agile pharmaceutical production paradigm that can respond to localized needs, providing personalized and precision medicine. These capabilities are critical for narrow therapeutic index
Nowrin Akter Surovi, Paul Witherell, Kumara Sundar, Vinay Saji Mathew
Additive Manufacturing (AM) is becoming increasingly popular in academia and industry due to its cost-effectiveness and time-saving benefits. However, AM faces several challenges that must be addressed to enhance its efficiency. While Machine Learning (ML)
The solidification behavior and crystallographic texture of 316L austenitic stainless steel builds fabricated via laser-wire directed energy deposition additive manufacturing (AM) were investigated. Shielding gas set-up and build type (single-track vs
Nicholas O'Brien, Syed Uddin, Jordan Weaver, Jake Jones, Satbir Singh, Jack Beuth
This work focuses on how spatter particles are transported within a laser powder bed fusion (L-PBF) machine. The machine's gas flow rate and salient flow features are studied with a computational fluid dynamics (CFD) model and are validated with
Stian Romberg, Paul Roberts, Chad R. Snyder, Anthony Kotula
Simultaneous rheology and conversion measurements of neat and composite epoxy resins reveal that conventional models neither accurately nor fully describe the relationship between rheology and conversion. We find that models predicting thermoset conversion
Jake Read, Jonathan Seppala, Filippos Tourlomousis, James Warren, Nicole Bakker, Neil Gershenfeld
Abstract To describe a new method for the automatic generation of process parameters for fused filament fabrication (FFF) across varying machines and materials. We use an instrumented extruder to fit a function that maps nozzle pressures across varying
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
Zhuo Yang, Jaehyuk Kim, Yan Lu, Albert T. Jones, Paul Witherell, Ho Yeung, Hyunwoong Yang
Metal powder bed fusion-based additive manufacturing (AM) processes have gained widespread adoption for producing complex parts with high performance. However, a multitude of factors still affect the build process, which leads to great challenges in
Metal Additive Manufacturing (MAM) is a transformative technology with the potential to revolutionize manufacturing through the production of complex, high-value components with unprecedented design freedom. However, the adoption of MAM is challenging due
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
Eric Whitenton, Alkan Donmez, Aniruddha Das, Vipin Tondare, Justin Whiting
Additive manufacturing is a rapidly growing and increasingly important set of manufacturing techniques. One of those techniques, powder bed fusion, is often used when making metal parts. The part is built up by spreading a thin layer of metal powder
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
Brian Simonds, Jack Tanner, Alexandra Artusio-Glimpse, Niranjan Parab, Cang Zhao, Tao Sun, Paul A. Williams
The 2022 Asynchronous AM-Bench challenge was designed to test the ability of simulations to accurately predict laser power absorption as well as various melt pool behaviors (width, depth, and solidification) during laser melting of solid metal during
Additive manufacturing, or 3D printing, is quickly becoming a widespread manufacturing method offering timely and cost-effective build times for unique part geometries with an increasing range of material offerings. One unique use for additive
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
Runbo Jiang, John Smith, Yu-Tsen Yi, Tao Sun, Brian Simonds, Anthony D. Rollett
The quantification of the amount of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additive manufactured metal components. The geometry of a vapor depression, also known as a
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
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
Fahad Milaat, Paul Witherell, Ho Yeung, Martin Hardwick
Traditionally, inspection and geometric dimensioning and tolerancing (GD&T) are deployed at the macroscale, where complete parts are tested to meet geometric and functional requirements. The additive manufacturing (AM) process is unique in that it is a
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
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
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
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