The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Cloud manufacturing: a new manufacturing paradigm
Abstract
Combining with the emerged technologies such as cloud computing, the Internet of things, service-oriented technologies and high performance computing, a new manufacturing paradigm – cloud manufacturing (CMfg) – for solving the bottlenecks in the informatisation development and manufacturing applications is introduced. The concept of CMfg, including its architecture, typical characteristics and the key technologies for implementing a CMfg service platform, is discussed. Three core components for constructing a CMfg system, i.e. CMfg resources, manufacturing cloud service and manufacturing cloud are studied, and the constructing method for manufacturing cloud is investigated. Finally, a prototype of CMfg and the existing related works conducted by the authors' group on CMfg are briefly presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Industrial Product-Service Systems—IPS 2
Meier, H., Roy, R., & Seliger, G. (2010) · CIRP Annals · doi:10.1016/j.cirp.2010.05.004 · Cited by 994
Cited by
Literature review of Industry 4.0 and related technologies
Oztemel, E., & Gursev, S. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-018-1433-8 · Cited by 2,143
Kusiak, A. (2018) · International Journal of Production Research · doi:10.1080/00207543.2017.1351644 · Cited by 1,330
Industrial artificial intelligence for industry 4.0-based manufacturing systems
Lee, J., Davari, H., Singh, J., & Pandhare, V. (2018) · Manufacturing Letters · doi:10.1016/j.mfglet.2018.09.002 · Cited by 870
A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin
Liu, Y., Zhang, L., Yang, Y., Zhou, L., Ren, L., Wang, F., Liu, R., Pang, Z., & Deen, M. J. (2019) · IEEE Access · doi:10.1109/access.2019.2909828 · Cited by 763
Self-citationIoT-Based Intelligent Perception and Access of Manufacturing Resource Toward Cloud Manufacturing
Tao, F., Zuo, Y., Xu, L. D., & Zhang, L. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2306397 · Cited by 587
Self-citationExplore success factors that impact artificial intelligence adoption on telecom industry in China
Chen, H., Li, L., & Chen, Y. (2021) · Journal of Management Analytics · doi:10.1080/23270012.2020.1852895 · Cited by 300
Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect
Hu, L., Nguyen, N.-T., Tao, W., Leu, M. C., Liu, X. F., Shahriar, M. R., & Al Sunny, S. M. N. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.07.155 · Cited by 219
A cloud-based supply chain management system: effects on supply chain responsiveness
Giannakis, M., Spanaki, K., & Dubey, R. (2019) · Journal of Enterprise Information Management · doi:10.1108/jeim-05-2018-0106 · Cited by 149
Fang, C., Liu, X., Pardalos, P. M., & Pei, J. (2016) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-015-7593-1 · Cited by 102
Enterprise modelling: Research review and outlook
Vernadat, F. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103265 · Cited by 92
Metadata
- Authors
- Zhang, L., Luo, Y., Tao, F., Li, B. H., Ren, L., Zhang, X., Guo, H., Cheng, Y., Hu, A., & Liu, Y.
- Venue
- Enterprise Information Systems
- Publisher
- Informa UK Limited
- Published
- 2012-05-21
- Volume
- 8
- Issue
- 2
- Pages
- 167-187
- ISSN
- 1751-7575 (ISSN-L)
- 1751-7583
- OpenAlex
- W2131077880
- Cited by
- 810
- References
- 1
- FWCI
- 124.36
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.