Influence analysis and low carbon evaluation of 3D sand printing process parameters on efficiency, resource consumption, and carbon emission

Jun Zheng, Feng Lin, Junjie Shi, Xinyu Hu, Qi Pan, Tiening Qi, Yicheng Ren, Aizhi Guan, Zhiyi Zhang and Wei Ling

Energy & Environment, 2024, vol. 35, issue 5, 2608-2635

Abstract: The 3D sand printing (3DSP) technology provides a richer realization path for the sustainable development of the manufacturing industry. It has the advantages of one-time molding, reducing design constraints and machining amount, and easy control of casting dimensional accuracy. Therefore, studying the impact of process parameters of the printing process on printing efficiency, resource consumption, and carbon emissions is the basis for the sustainable development of 3DSP technology. In this paper, starting from the main influencing parameters such as printing layer thickness, recoater speed, printing angle, and single printing quantity, a relationship model between printing parameters and carbon emission sources is constructed. A total factor carbon emission prediction model of 3DSP process including the impact of capital and labor is established. Build an influence relationship with printing parameters as independent variables and carbon emissions as dependent variables. Taking the sand casting industry as an example to verify the above model, the experimental results show that the thickness of the printing layer has the greatest impact on carbon emissions. When the layer thickness is 0.36 mm, the speed of the recoater is 0.22 m/s, the printing angle is (0°, 0°, 90°), and the single print quantity is 84, the total carbon emission is the lowest and 28.77% less compared to the parameter with the highest carbon emission. The average relative error of the predictive model is 1.929%. The results of this study can provide some new ideas for sustainable development of additive manufacturing technology.

Keywords: 3D sand printing; low carbon evaluation; printing parameters; sustainable manufacturing; influence analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:engenv:v:35:y:2024:i:5:p:2608-2635

DOI: 10.1177/0958305X231153942

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