The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services
Abstract
Abstract Making manufacturing as on-demand cloud services is a transformative paradigm to achieve the required business flexibility in the context of Industry 4.0 via enabling rapid configuration of loosely-connected manufacturing devices to develop highly customized products. The research in this paper aimed to fill the gap that there is a lack of a feasible solution for cloud-based manufacturing equipment that can provide on-demand manufacturing services accessible via the Internet. The technical challenges in developing cloud-based manufacturing equipment and the enabling technologies are discussed. A generic system architecture for cloud-based manufacturing equipment based on cyber-physical production systems and big data analytics is proposed, allowing manufacturing equipment to be connected to the cloud and made available for the provision of on-demand manufacturing services. An industry implementation in a world-leading machinery solution provider confirms that the proposed system architecture for cloud-based manufacturing equipment can successfully enable on-demand manufacturing services provisioned via the Internet and can be extended to businesses that endeavor to transform legacy production systems into cloud-based cyber-physical production systems.
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Citations
Cites
Software-defined Cloud Manufacturing for Industry 4.0
Thames, L., & Schaefer, D. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.07.041 · Cited by 410
Cybersecurity for Industry 4.0: Analysis for Design and Manufacturing
(2017) · Springer Series in Advanced Manufacturing · doi:10.1007/978-3-319-50660-9 · Cited by 162
Wu, Z., Meng, Z., & Gray, J. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2704613 · Cited by 40
Cited by
Lim, K. Y. H., Zheng, P., & Chen, C.-H. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01512-w · Cited by 700
Lu, Y., Xu, X., & Wang, L. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.010 · Cited by 528
Self-citationArtificial intelligence, cyber-threats and industry 4.0: challenges and opportunities
Bécue, A., Praça, I., & Gama, J. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-020-09942-2 · Cited by 368
A review of industrial big data for decision making in intelligent manufacturing
Li, C., Chen, Y., & Shang, Y. (2022) · Engineering Science and Technology, an International Journal · doi:10.1016/j.jestch.2021.06.001 · Cited by 325
Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems
Liu, C., Le Roux, L., Körner, C., Tabaste, O., Lacan, F., & Bigot, S. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.010 · Cited by 252
Metadata
- Authors
- Lu, Y., & Xu, X.
- Venue
- Robotics and Computer-Integrated Manufacturing
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 57
- Pages
- 92-102
- ISSN
- 0736-5845 (ISSN-L)
- OpenAlex
- W2902323097
- Cited by
- 294
- References
- 3
- FWCI
- 26.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lu, Y., & Xu, X. (2019). Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services. Robotics and Computer-Integrated Manufacturing. https://doi.org/10.1016/j.rcim.2018.11.006
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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.
