The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.
Big data for cyber physical systems in industry 4.0: a survey
Abstract
With the technology development in cyber physical systems and big data, there are huge potential to apply them to achieve personalization and improve resource efficiency in Industry 4.0. As Industry 4.0 is the relatively new concept originated from an advanced manufacturing vision supported by the German government in 2011, there are only several existing surveys on either cyber physical systems or big data in Industry 4.0. In addition, there are much less surveys related to the intersection between cyber physical systems and big data in Industry 4.0. However, cyber physical systems are closely related to big data in nature. For example, cyber physical systems will continuously generate a large amount of data which requires the big data techniques to process and help to improve system scalability, security, and efficiency. Therefore, we conduct this survey to bring more attention to this critical intersection and highlight the future research direction to achieve the fully autonomy in Industry 4.0.
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Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890
Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics
Lu, Y., & Xu, L. D. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2869847 · Cited by 567
Self-citationIndustry 4.0: A Solution towards Technology Challenges of Sustainable Business Performance
Haseeb, M., Hussain, H. I., Ślusarczyk, B., & Jermsittiparsert, K. (2019) · Social Sciences · doi:10.3390/socsci8050154 · Cited by 459
Sony, M., & Naik, S. (2020) · Production Planning & Control · doi:10.1080/09537287.2019.1691278 · Cited by 401
Augmented reality in support of intelligent manufacturing – A systematic literature review
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Metadata
- Authors
- Xu, L. D., & Duan, L.
- Venue
- Enterprise Information Systems
- Publisher
- Informa UK Limited
- Published
- 2018-03
- Volume
- 13
- Issue
- 2
- Pages
- 148-169
- ISSN
- 1751-7575 (ISSN-L)
- 1751-7583
- OpenAlex
- W2790282462
- Cited by
- 526
- References
- 143
- FWCI
- 64.59
- Type
- journal article
- Language
- en
- Open access
- closed
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