Simulation-assisted multi-process integrated optimization for greentelligent aluminum casting
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DOI: 10.1016/j.apenergy.2023.120831
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- Konstantinos Salonitis & Mark Jolly & Emanuele Pagone & Michail Papanikolaou, 2019. "Life-Cycle and Energy Assessment of Automotive Component Manufacturing: The Dilemma Between Aluminum and Cast Iron," Energies, MDPI, vol. 12(13), pages 1-23, July.
- Liu, Weipeng & Peng, Tao & Kishita, Yusuke & Umeda, Yasushi & Tang, Renzhong & Tang, Wangchujun & Hu, Luoke, 2021. "Critical life cycle inventory for aluminum die casting: A lightweight-vehicle manufacturing enabling technology," Applied Energy, Elsevier, vol. 304(C).
- Gang Liu & Colton E. Bangs & Daniel B. Müller, 2013. "Stock dynamics and emission pathways of the global aluminium cycle," Nature Climate Change, Nature, vol. 3(4), pages 338-342, April.
- Sun, Wenqiang & Wang, Qiang & Zhou, Yue & Wu, Jianzhong, 2020. "Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives," Applied Energy, Elsevier, vol. 268(C).
- Tian, Shuoshuo & Di, Yuezhong & Dai, Min & Chen, Weiqiang & Zhang, Qi, 2022. "Comprehensive assessment of energy conservation and CO2 emission reduction in future aluminum supply chain," Applied Energy, Elsevier, vol. 305(C).
- Haraldsson, Joakim & Johansson, Maria T., 2018. "Review of measures for improved energy efficiency in production-related processes in the aluminium industry – From electrolysis to recycling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 525-548.
- Xi, Han & Wu, Xiao & Chen, Xianhao & Sha, Peng, 2021. "Artificial intelligent based energy scheduling of steel mill gas utilization system towards carbon neutrality," Applied Energy, Elsevier, vol. 295(C).
- Liu, Weipeng & Peng, Tao & Tang, Renzhong & Umeda, Yasushi & Hu, Luoke, 2020. "An Internet of Things-enabled model-based approach to improving the energy efficiency of aluminum die casting processes," Energy, Elsevier, vol. 202(C).
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- Ma, Shuaiyin & Huang, Yuming & Liu, Yang & Kong, Xianguang & Yin, Lei & Chen, Gaige, 2023. "Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries," Applied Energy, Elsevier, vol. 337(C).
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Keywords
Aluminum casting; Carbon neutrality; Operation optimization; Green manufacturing; Intelligent manufacturing;All these keywords.
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