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    Integrating Graph Retrieval-Augmented Generation With Large Language Models for Supplier Discovery 

    Source: Journal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue: 002:;page 21010-1
    Author(s): Li, Yunqing; Ko, Hyunwoong; Ameri, Farhad
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As supply chain complexity and dynamism challenge traditional management approaches, integrating large language models (LLMs) and knowledge graphs (KGs) emerges as a promising method for advancing supply chain analytics. ...
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    Diffusion Modeling-Based Generative Multimodal Data Fusion for Aerosol Jet Electronics Printing 

    Source: Journal of Computing and Information Science in Engineering:;2026:;volume( 026 ):;issue:007:;page 9982
    Author(s): Lee, Suk Ki; Elhambakhsh, Fatemeh; Ko, Hyunwoong
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. The rising demand for high-value electronics necessitates advanced manufacturing techniques capable of meeting stringent specifications for precise, complex, and compact devices, driving the shift toward innovative ...
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    A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis 

    Source: Journal of Computing and Information Science in Engineering:;2019:;volume( 019 ):;issue: 004:;page 41014
    Author(s): Kim, Samyeon; Rosen, David W.; Witherell, Paul; Ko, Hyunwoong
    Publisher: American Society of Mechanical Engineers (ASME)
    Abstract: Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure the manufacturability of parts fabricated using additive manufacturing (AM) processes. However, ...
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    Transferability Analysis of Data-Driven Additive Manufacturing Knowledge: A Case Study Between Powder Bed Fusion and Directed Energy Deposition 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 005:;page 51011-1
    Author(s): Safdar, Mutahar; Xie, Jiarui; Ko, Hyunwoong; Lu, Yan; Lamouche, Guy; Zhao, Yaoyao Fiona
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Data-driven research in additive manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature emerging. The knowledge in these works consists of AM and artificial ...
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    Enhancing Part Quality Management Using a Holistic Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 005:;page 51008-1
    Author(s): Yang, Zhuo; Kim, Jaehyuk; Lu, Yan; Jones, Albert; Witherell, Paul; Yeung, Ho; Ko, Hyunwoong
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Metal powder bed fusion additive manufacturing (AM) processes have gained widespread adoption for the ability to produce complex geometries with high performance. However, a multitude of factors still affect the build ...
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    Generative Model Predictive Control in Manufacturing Processes: A Review 

    Source: Journal of Computing and Information Science in Engineering:;2026:;volume( 026 ):;issue:008
    Author(s): Lee, Suk Ki; Stone, Ronnie F. P.; Gao, Max; Zhang, Wenlong; Sha, Zhenghui; Ko, Hyunwoong
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. Manufacturing processes are inherently dynamic and uncertain, with varying parameters and nonlinear behaviors, making robust control essential for maintaining quality and reliability. Traditional control methods ...
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    Functional Requirements of Software Tools for Laser-Based Powder Bed Fusion Additive Manufacturing for Metals 

    Source: Journal of Computing and Information Science in Engineering:;2022:;volume( 023 ):;issue: 003:;page 31005
    Author(s): Feng, Shaw C.;Moges, Tesfaye;Park, Hyunseop;Yakout, Mostafa;Jones, Albert T.;Ko, Hyunwoong;Witherell, Paul
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Additive manufacturing (AM) for metals is rapidly transitioning to an accepted production technology, which has led to increasing demands for data analysis and software tools. The performance of laser-based powder bed ...
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