A Study on the Transformation of Smart Manufacturing in Steel Enterprises in Guangdong Province, China Based on Digitalization, Intelligence and Other Factors
Keywords:
transformation and upgrading, intelligent manufacturing, influencing factors, process intelligenceAbstract
With the development and progress of China's society and economy, Chinese iron and steel enterprises, as a traditional heavy industry, are developing more and more scale, and once faced the problem of serious overcapacity. Transformation and upgrading should be actively pursued. This paper focuses on the relationship between the main factors affecting the transformation and upgrading of the steel industry in Guangdong Province, China based on the background technology of intelligent manufacturing, technological innovation, new changes in the development of intelligent manufacturing, and new trends in process intelligence. Make a judgment based on the trend: data will become the core element of the intelligent development of the manufacturing industry in the new era. Process intelligence will become an important breakthrough in the development of intelligent manufacturing in the new era. New intelligent manufacturing equipment will become an important driving force for the development of intelligent manufacturing in the new era.
References
Government department documents. 14th Five-Year Plan for the Development of Intelligent Manufacturing. 2021.
Liu Hengwen. Research on SG Steel Company Intelligent Manufacturing Strategy. 10.27272/d.cnki.gshdu.2021.001175.
Agus Purwanto, John Tampil Purba, Innocentius Bernarto, Rosdiana Sijabat. The Role of Transformational Leadership, Organizational Citizenship Behaviour, Innovative Work Behaviour, Quality Work Life, Digital Transformation and Leader Member Exchange on Universities Performance. LINGUISTICA ANTVERPIENSIA, 2021 Issue-2
Huang Z, Shen Y.A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics .AI-Driven Digital Twins. Sensors 2021, 21, 6340.
Han Lu. Mechanism and Decision-making Models of Manufacturing Enterprise Supply Chain Digitalization. Doctoral Dissertation of Beijing Jiaotong University, 10.26944/d.cnki.gbfju.2022.000204.
Dorota Stadnicka,Pawel Litwin,Dario Antonelli.Human factor in intelligent manufacturing systems - knowledge acquisition and motivation.Science Direct.2019.02.023.
Dietmar P. F. Möller.Enhancement in Intelligent Manufacturing through Circular Economy.2020 IEEE International Conference on Electro Information Technology (EIT).10.1109/EIT48999.2020.9208321
Limeng Ying, Xiaojing Liu, Menghao Li. How does intelligent manufacturing affects enterprise innovation. The mediating role of organisational learning. Enterprise Information Systems. 22 Jun 2022.
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Copyright (c) 2023 Yong Shi, PC Lai

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Published by University Tun Abdul Razak (UNIRAZAK)
