期刊
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
卷 167, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2021.120653
关键词
Industry 4.0; Fourth industrial revolution; Review; Survey; Text mining
资金
- National Research Foundation of Korea (Ministry of Education of the Republic of Korea) [NRF-2018S1A5A2A03032736]
- National Research Foundation of Korea (Ministry of Science and ICT) [NRF-2020R1F1A1076067]
- Institute of Information & Communications Technology Planning & Evaluation (IITP) - Korea government (MSIT) (Artificial Intelligence Graduate School Program - UNIST) [2020-0-01336]
This study identified and described 31 research and application issues related to Industry 4.0, and proposed a framework for convergence in Industry 4.0. The research outcomes were consistent with existing discussions on Industry 4.0, validating the utility of the data-driven approach. This work helps establish a common understanding of Industry 4.0 and enables further research and development for industrial innovation and social advance.
Industry 4.0 has attracted considerable interest from firms, governments, and individuals as the new concept of future computer, industrial, and social systems. However, the concept has yet to be fully explored in the scientific literature. Given the topic's broad scope, this work attempts to understand and clarify Industry 4.0 by analyzing 660 journal papers and 3,901 news articles through text mining with unsupervised machine learning algorithms. Based on the results, this work identifies 31 research and application issues related to Industry 4.0. These issues are categorized and described within a five-level hierarchy: 1) infrastructure development for connection, 2) artificial intelligence development for data-driven decision making, 3) system and process optimization, 4) industrial innovation, and 5) social advance. Further, a framework for convergence in Industry 4.0 is proposed, featuring six dimensions: connection, collection, communication, computation, control, and creation. The research outcomes are consistent with and complementary to existing relevant discussion and debate on Industry 4.0, which validates the utility and efficiency of the data-driven approach of this work to support experts' insights on Industry 4.0. This work helps establish a common ground for understanding Industry 4.0 across multiple disciplinary perspectives, enabling further research and development for industrial innovation and social advance.
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