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    Digital Twin-Driven Product Sustainable Design for Low Carbon Footprint

    Source: Journal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 006::page 60805-1
    Author:
    He, Bin
    ,
    Mao, Hangyu
    DOI: 10.1115/1.4062427
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Product sustainability is a pressing global issue that requires urgent improvement, and low-carbon design is a crucial approach toward achieving sustainable product development. Digital twin technology, which connects the physical and virtual worlds, has emerged as an effective tool for supporting product design and development. However, obtaining accurate product parameters remains a challenge, and traditional low-carbon product design primarily focuses on design parameters. To address these issues, this paper proposes a method for data collection throughout the product lifecycle, leveraging the Internet of Things. The paper envisions the automatic collection of product lifecycle data to enhance the accuracy of product design. Moreover, traditional low-carbon design often has a limited scope that primarily considers product structure and lifecycle stage for optimization. In contrast, combining digital twin technology with low-carbon design can effectively improve product sustainability. Therefore, this paper proposes a three-layer architecture model of product sustainability digital twin, comprising data layer, mapping layer, and application layer. This model sets the carbon footprint as the iterative optimization goal and facilitates the closed-loop sustainable design of the product. The paper envisions sustainable product design based on digital twins that can address cascading problems and achieve closed-loop sustainable design.
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      Digital Twin-Driven Product Sustainable Design for Low Carbon Footprint

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4294505
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    contributor authorHe, Bin
    contributor authorMao, Hangyu
    date accessioned2023-11-29T18:58:53Z
    date available2023-11-29T18:58:53Z
    date copyright5/25/2023 12:00:00 AM
    date issued5/25/2023 12:00:00 AM
    date issued2023-05-25
    identifier issn1530-9827
    identifier otherjcise_23_6_060805.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294505
    description abstractProduct sustainability is a pressing global issue that requires urgent improvement, and low-carbon design is a crucial approach toward achieving sustainable product development. Digital twin technology, which connects the physical and virtual worlds, has emerged as an effective tool for supporting product design and development. However, obtaining accurate product parameters remains a challenge, and traditional low-carbon product design primarily focuses on design parameters. To address these issues, this paper proposes a method for data collection throughout the product lifecycle, leveraging the Internet of Things. The paper envisions the automatic collection of product lifecycle data to enhance the accuracy of product design. Moreover, traditional low-carbon design often has a limited scope that primarily considers product structure and lifecycle stage for optimization. In contrast, combining digital twin technology with low-carbon design can effectively improve product sustainability. Therefore, this paper proposes a three-layer architecture model of product sustainability digital twin, comprising data layer, mapping layer, and application layer. This model sets the carbon footprint as the iterative optimization goal and facilitates the closed-loop sustainable design of the product. The paper envisions sustainable product design based on digital twins that can address cascading problems and achieve closed-loop sustainable design.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDigital Twin-Driven Product Sustainable Design for Low Carbon Footprint
    typeJournal Paper
    journal volume23
    journal issue6
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4062427
    journal fristpage60805-1
    journal lastpage60805-8
    page8
    treeJournal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 006
    contenttypeFulltext
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