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Lim, Chiehyeon
Service Engineering & Knowledge Discovery Lab
Research Interests
  • Smart service systems, Service-oriented data analytics, Service operations, Service design, Decision science, Personal process management

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From technological development to social advance: A review of Industry 4.0 through machine learning

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dc.contributor.author Lee, Changhun ko
dc.contributor.author Lim, Chiehyeon ko
dc.date.available 2021-03-04T01:43:20Z -
dc.date.created 2021-03-02 ko
dc.date.issued 2021-06 ko
dc.identifier.citation TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, v.167, pp.120653 ko
dc.identifier.issn 0040-1625 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/50062 -
dc.description.abstract 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. ko
dc.language 영어 ko
dc.publisher Elsevier BV ko
dc.title From technological development to social advance: A review of Industry 4.0 through machine learning ko
dc.type ARTICLE ko
dc.type.rims ART ko
dc.identifier.doi 10.1016/j.techfore.2021.120653 ko
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S0040162521000858 ko
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