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    A Digital Twin–Based Environment-Adaptive Assignment Method for Human–Robot Collaboration 

    Source: Journal of Manufacturing Science and Engineering:;2023:;volume( 146 ):;issue: 003:;page 31004-1
    Author(s): Ma, Xin; Qi, Qinglin; Tao, Fei
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Human–robot collaboration, which strives to combine the best skills of humans and robots, has shown board application prospects in meeting safe–effective–flexible requirements in various fields. The ideation of much closer ...
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    An Extensible Model for Multitask-Oriented Service Composition and Scheduling in Cloud Manufacturing 

    Source: Journal of Computing and Information Science in Engineering:;2016:;volume( 016 ):;issue: 004:;page 41009
    Author(s): Liu, Yongkui; Xu, Xun; Zhang, Lin; Tao, Fei
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Cloud manufacturing is an emerging novel business paradigm for the manufacturing industry. In cloud manufacturing, distributed manufacturing resources are encapsulated into services and aggregated in a cloud manufacturing ...
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    Partial/Parallel Disassembly Sequence Planning for Complex Products 

    Source: Journal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 001:;page 11016
    Author(s): Tao, Fei; Bi, Luning; Zuo, Ying; Nee, A. Y. C.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Disassembly is a very important step in recycling and maintenance, particularly for energy saving. However, disassembly sequence planning (DSP) is a challenging combinatorial optimization problem due to complex constraints ...
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    A Cooperative Co-Evolutionary Algorithm for Large-Scale Process Planning With Energy Consideration 

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 006:;page 61016
    Author(s): Tao, Fei; Bi, Luning; Zuo, Ying; Nee, A. Y. C.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Process planning can be an effective way to improve the energy efficiency of production processes. Aimed at reducing both energy consumption and processing time (PT), a comprehensive approach that considers feature sequencing, ...
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    Learning Nonlinear Constitutive Laws Using Neural Network Models Based on Indirectly Measurable Data 

    Source: Journal of Applied Mechanics:;2020:;volume( 087 ):;issue: 008
    Author(s): Liu, Xin; Tao, Fei; Du, Haodong; Yu, Wenbin; Xu, Kailai
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Artificial neural network (ANN) models are used to learn the nonlinear constitutive laws based on indirectly measurable data. The real input and output of the ANN model are derived from indirect data using a mechanical ...
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    Failure Prognosis of Complex Equipment With Multistream Deep Recurrent Neural Network 

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 002
    Author(s): Su, Yonghe; Tao, Fei; Jin, Jian; Wang, Tian; Wang, Qingguo; Wang, Lei
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The failure prognosis is crucial for industrial equipment in prognostics and health management field. The vibration signal is the commonly used data for failure prognosis. The conventional prognostic approaches have ...
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    Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process 

    Source: Journal of Manufacturing Science and Engineering:;2024:;volume( 147 ):;issue: 004:;page 41005-1
    Author(s): Zhu, Yonghuai; Zhou, Xiaoya; Cheng, Jiangfeng; Liu, Zhifeng; Zou, Xiaofu; Cheng, Qiang; Xu, Hui; Wang, Yong; Tao, Fei
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Various remaining useful life (RUL) prediction methods, encompassing model-based, data-driven, and hybrid methods, have been developed and successfully applied to prognostics and health management for diverse rolling ...
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    Energy-Aware Material Selection for Product With Multicomponent Under Cloud Environment 

    Source: Journal of Computing and Information Science in Engineering:;2017:;volume( 017 ):;issue: 003:;page 31007
    Author(s): Bi, Luning; Zuo, Ying; Tao, Fei; Liao, T. W.; Liu, Zhuqing
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Energy consumption in manufacturing has risen to be a global concern. Material selection in the product design phase is of great significance to energy conservation and emission reduction. However, because of the limitation ...
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    Manufacturing Service Management in Cloud Manufacturing: Overview and Future Research Directions 

    Source: Journal of Manufacturing Science and Engineering:;2015:;volume( 137 ):;issue: 004:;page 40912
    Author(s): Tao, Fei; Zhang, Lin; Liu, Yongkui; Cheng, Ying; Wang, Lihui; Xu, Xun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As a new serviceoriented manufacturing paradigm, cloud manufacturing (CMfg) has experienced rapid development in the past five years. The research on its theories, key technologies, developments, and applications still ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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