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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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