• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2023, Vol. 59 ›› Issue (7): 225-240.doi: 10.3901/JME.2023.07.225

Special Issue: 《机械工程学报》近期佳作集锦 | “双碳”绿色制造技术

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Research Status and Technology Path of Low-carbon Manufacturing under the Background of Emission Peak and Carbon Neutrality

LI Hongcheng1,2, CAO Huajun3, LIU Lanwei2, XING Bin2, PAN Xin4, WEN Xuanhao3, GE Weiwei3   

  1. 1. School of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunication, Chongqing 400065;
    2. Chongqing Industrial Big Data Innovation Center Co. Ltd., Chongqing 400700;
    3. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044;
    4. COMAC Shanghai Aircraft Manufacturing Co., Ltd., Shanghai 201324
  • Received:2022-06-01 Revised:2022-12-09 Online:2023-04-05 Published:2023-06-16

Abstract: Through the analysis of the development of low-carbon manufacturing at home and abroad, the connotation and theoretical system of low-carbon manufacturing are systematically discussed. The research status of low-carbon manufacturing technology innovation at home and abroad is then analyzed from several aspects, such as carbon emissions accounting and carbon footprint assessment, low-carbon product design and development, low-carbon manufacturing process and equipment, data-driven carbon emission dynamic monitoring, low-carbon optimized operation of manufacturing systems, carbon efficiency optimization and lean control of manufacturing process, and low-carbon manufacturing paradigm. Under the background of emission peak and carbon neutrality, the low-carbon manufacturing technology path of "carbon emissions accounting, carbon emissions diagnosis and carbon emissions reduction" based on the new generation of information technologies such as industrial internet and big data has been proposed, accordingly the industrial carbon emissions big data platform has also been established.

Key words: low-carbon manufacturing, carbon emissions accounting, carbon emissions diagnosis, carbon emissions reduction, industrial carbon emissions big data

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