Open AccessDynamic Monitoring Method of Enterprise Power Consumption Based on Energy Big Data
Author(s) -
Jiangtao Guo,
Yajie Li,
Ming Fan,
Wanzhen Ma
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2254/1/012022
Subject(s) - discrete manufacturing , energy consumption , process (computing) , environmental pollution , environmental economics , manufacturing , manufacturing engineering , consumption (sociology) , efficient energy use , economic shortage , production (economics) , energy management , control (management) , quality (philosophy) , energy (signal processing) , business , operations management , computer science , engineering , environmental science , economics , marketing , social science , philosophy , mathematics , artificial intelligence , government (linguistics) , macroeconomics , linguistics , sociology , operating system , environmental protection , epistemology , statistics , electrical engineering
With the global shortage of resources and energy and the intensification of environmental pollution, the problems of energy consumption and pollution emission in the manufacturing industry have become increasingly prominent. Green development, quality improvement and efficiency increase have gradually become an important development trend of the manufacturing industry. Green manufacturing engineering must be vigorously constructed and developed. Discrete manufacturing is characterized by discontinuous processes. The manufacturing process is accompanied by a large amount of primary energy consumption and environmental emissions. Compared with process manufacturing, discrete manufacturing process control is more complex and changeable, its green development level needs to be improved, and the implementation process is more difficult. As one of the common workshops in discrete manufacturing, NC workshop has problems such as high energy consumption. Based on the above reasons, this paper takes the energy-saving optimization and energy management of discrete manufacturing enterprises as the research goal, and carries out the research on energy-saving optimization and energy management system for NC workshop. It is of great significance to reduce the energy consumption of NC workshop, improve the energy utilization efficiency, solve the pain points of many enterprise information islands and difficult to control energy consumption, and improve the green level of production process in discrete manufacturing enterprises.