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    A Blockchain-Based G-Code Protection Approach for Cyber-Physical Security in Additive Manufacturing 

    Source: Journal of Computing and Information Science in Engineering:;2021:;volume( 021 ):;issue: 004:;page 041007-1
    Author(s): Shi, Zhangyue; Kan, Chen; Tian, Wenmeng; Liu, Chenang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As an emerging technology, additive manufacturing (AM) is able to fabricate products with complex geometries using various materials. In particular, cyber-enabled AM systems have recently become widely applied in many ...
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    Assessing Impact of Understory Vegetation Density on Solid Obstacle Detection for Off-Road Autonomous Ground Vehicles 

    Source: ASME Letters in Dynamic Systems and Control:;2020:;volume( 001 ):;issue: 002:;page 021008-1
    Author(s): Foroutan, Morteza; Tian, Wenmeng; Goodin, Christopher T.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In autonomous driving systems, advanced sensing technologies (such as Light Detection and Ranging (LIDAR) devices and cameras) can capture high volume of data for real-time traversability analysis. Off-road autonomy is ...
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    Design De-Identification of Thermal History for Collaborative Process-Defect Modeling of Directed Energy Deposition Processes 

    Source: Journal of Manufacturing Science and Engineering:;2023:;volume( 145 ):;issue: 005:;page 51004-1
    Author(s): Fullington, Durant; Bian, Linkan; Tian, Wenmeng
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: There is an urgent need for developing collaborative process-defect modeling in metal-based additive manufacturing (AM). This mainly stems from the high volume of training data needed to develop reliable machine learning ...
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    Adaptive Thermal History De-Identification for Privacy-Preserving Data Sharing of Directed Energy Deposition Processes 

    Source: Journal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue: 003:;page 31006-1
    Author(s): Bappy, Mahathir Mohammad; Fullington, Durant; Bian, Linkan; Tian, Wenmeng
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In collaborative additive manufacturing (AM), sharing process data across multiple users can provide small- to medium-sized manufacturers (SMMs) with enlarged training data for part certification, facilitating accelerated ...
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    Data-Driven Energy Efficiency and Part Geometric Accuracy Modeling and Optimization of Green Fused Filament Fabrication Processes 

    Source: Journal of Mechanical Design:;2020:;volume( 142 ):;issue: 004:;page 041701-1
    Author(s): Alizadeh, Morteza; Esfahani, Mehrnaz Noroozi; Tian, Wenmeng; Ma, Junfeng
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Nowadays, increasing awareness of environmental protection has evoked the adoption of green technologies in design and manufacturing. As a revolutionizing manufacturing technology that produces components in a layer-by-layer ...
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    Understanding the Effects of Process Conditions on Thermal–Defect Relationship: A Transfer Machine Learning Approach 

    Source: Journal of Manufacturing Science and Engineering:;2023:;volume( 145 ):;issue: 007:;page 71010-1
    Author(s): Senanayaka, Ayantha; Tian, Wenmeng; Falls, T. C.; Bian, Linkan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This study aims to develop an intelligent, rapid porosity prediction methodology for additive manufacturing (AM) processes under varying process conditions by leveraging knowledge transfer from the existing process conditions. ...
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    Diffusion Generative Model-Based Learning for Smart Layer-Wise Monitoring of Additive Manufacturing 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 006:;page 60903-1
    Author(s): Yangue, Emmanuel; Fullington, Durant; Smith, Owen; Tian, Wenmeng; Liu, Chenang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Despite the rapid adoption of deep learning models in additive manufacturing (AM), significant quality assurance challenges continue to persist. This is further emphasized by the limited availability of sample objects for ...
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    Morphological Dynamics-Based Anomaly Detection Towards In Situ Layer-Wise Certification for Directed Energy Deposition Processes 

    Source: Journal of Manufacturing Science and Engineering:;2022:;volume( 144 ):;issue: 011:;page 111007
    Author(s): Bappy, Mahathir Mohammad;Liu, Chenang;Bian, Linkan;Tian, Wenmeng
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The process uncertainty induced quality issue remains the major challenge that hinders the wider adoption of additive manufacturing (AM) technology. The defects occurred significantly compromise structural integrity and ...
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    Deep Multi-Modal U-Net Fusion Methodology of Thermal and Ultrasonic Images for Porosity Detection in Additive Manufacturing 

    Source: Journal of Manufacturing Science and Engineering:;2023:;volume( 145 ):;issue: 006:;page 61009-1
    Author(s): Zamiela, Christian; Jiang, Zhipeng; Stokes, Ryan; Tian, Zhenhua; Netchaev, Anton; Dickerson, Charles; Tian, Wenmeng; Bian, Linkan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We developed a deep fusion methodology of nondestructive in-situ thermal and ex-situ ultrasonic images for porosity detection in laser-based additive manufacturing (LBAM). A core challenge with the LBAM is the lack of ...
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    Sensor Data Protection Through Integration of Blockchain and Camouflaged Encryption in Cyber-Physical Manufacturing Systems 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 007:;page 71004-1
    Author(s): Shi, Zhangyue; Oskolkov, Boris; Tian, Wenmeng; Kan, Chen; Liu, Chenang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The advancement of sensing technology enables efficient data collection from manufacturing systems for monitoring and control. Furthermore, with the rapid development of the Internet of Things (IoT) and information ...
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