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Innovative product design method for low-carbon footprint based on multi-layer carbon footprint information

Author:
Peng, Jun, Li, Wenqiang, Li, Yan, Xie, Yuanming, Xu, Zilin
Source:
Journal of cleaner production 2019 v.228 pp. 729-745
ISSN:
0959-6526
Subject:
carbon footprint, greenhouse gases, models, washing
Abstract:
At present, analysis and design methods for a product’s carbon footprint are focused mostly on its existing structures, which are difficult to integrate with the conceptual design process of low-carbon, innovative products. To solve this problem, this study proposes a new low-carbon design method based on a multi-layer carbon footprint information model. The hierarchical carbon footprint information model is the combination of direct structural design elements with indirect design elements such as functions and principles. The study also proposes a method for qualitative/semi-quantitative carbon footprint calculation. To achieve this, design information is combined with product structure tree (PST) to form a greenhouse gas (GHG)-product structure tree (G-PST) based on the carbon footprint design information. The influence degree (Id) of each design element in the G-PST is evaluated by the analytical network process (ANP) method and the optimizable degree (Od) of each design element for low-carbon design is obtained. The low-carbon product design is divided into four categories—structure optimization design, principle optimization design, function optimization design, and process optimization design—and the corresponding innovative design strategies are proposed. The results of this research can effectively obtain and standardize various low-carbon design elements, and provide targeted methods and tools for guiding designers to implement innovative low-carbon designs. The effectiveness of this low-carbon design method proposed is then tested on a Haier automatic washing machine, EB72M2JD.
Agid:
6430522