The DOI matches its Crossref record; 110 of the 110 references it cites were found in a registry or an index.
A review of industrial big data for decision making in intelligent manufacturing
Open accessAbstract
Under the trend of economic globalization, intelligent manufacturing has attracted a lot of attention from academic and industry. Related enabling technologies make manufacturing industry more intelligent. As one of the key technologies in artificial intelligence, big data driven analysis improves the market competitiveness of manufacturing industry by mining the hidden knowledge value and potential ability of industrial big data, and helps enterprise leaders make wise decisions in various complex manufacturing environments. This paper provides a theoretical analysis basis for big data-driven technology to guide decision-making in intelligent manufacturing, fully demonstrating the practicability of big data-driven technology in the intelligent manufacturing industry, including key advantages and internal motivation. A conceptual framework of intelligent decision-making based on industrial big data-driven technology is proposed in this study, which provides valuable insights and thoughts for the severe challenges and future research directions in this field.
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Cites
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Implementing Smart Factory of Industrie 4.0: An Outlook
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A survey on deep learning for big data
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Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems
Alcácer, V., & Cruz-Machado, V. (2019) · Engineering Science and Technology, an International Journal · doi:10.1016/j.jestch.2019.01.006 · Cited by 1,063
A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements
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Cited by
Understanding Data Quality in a Data-Driven Industry Context: Insights from the Fundamentals
Fu, Q., Nicholson, G. L., & Easton, J. M. (2024) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2024.100729 · Cited by 17
Big Data Life Cycle in Shop-Floor–Trends and Challenges
Pulikottil, T., Estrada-Jimenez, L. A., Abadía, J. J. P., Carrera-Rivera, A., Torayev, A., Rehman, H. U., Mo, F., Nikghadam-Hojjati, S., & Barata, J. (2023) · IEEE Access · doi:10.1109/access.2023.3253286 · Cited by 14
Metadata
- Authors
- Li, C., Chen, Y., & Shang, Y.
- Venue
- Engineering Science and Technology, an International Journal
- Publisher
- Elsevier BV
- Published
- 2022-05
- Volume
- 29
- Pages
- 101021
- ISSN
- 2215-0986 (ISSN-L)
- OpenAlex
- W3177323237
- Cited by
- 325
- References
- 110
- FWCI
- 27.62
- Type
- journal article
- Language
- en
- Open access
- gold
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- Li, C., Chen, Y., & Shang, Y. (2022). A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal. https://doi.org/10.1016/j.jestch.2021.06.001
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
