期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 15, 期 6, 页码 3343-3355出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2018.2871167
关键词
Competition and cooperation; computational experiment; social learning evolution (SLE); social manufacturing
类别
资金
- National Key Research and Development Program of China [2017YFB1401200]
- National Natural Science Foundation of China [61832014, 41701133]
- Program for Science AMP
- Technology Innovation Talents of Henan Province [174100510008]
- Natural Science Foundation of Henan Province [162300410121, TII-18-1706]
As a new form of manufacturing industry in the Internet era, social manufacturing has its inherent socialcyber complexity: the source of manufacturing service is social, and such sociality aggravates the diversity, uncertainty, and dynamics of service supply. This poses new challenges to the service matching between supply-side and demand-side. In order to meet this challenge, it is necessary to conduct a complexity analysis of social manufacturing. Traditional researches mainly rely on data statistics and macro analysis, in which there are difficulties in clearly identifying the links between various impact factors and macro evolution phenomena. In order to change such a situation, this paper proposes a modeling framework of social manufacturing from the aspect of social learning evolution (SLE), including individual evolution model, organizational learning model, and social learning model. Based on the SLE framework, the corresponding computational experiment system is built to analyze the complexity of social manufacturing. The performance of several evolution mechanisms in social manufacturing is simulated and compared as a case study to present the application of SLE framework. The results demonstrate that our method has a substantial promise.
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