Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/21634Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Li, P | - |
| dc.contributor.author | Cheng, K | - |
| dc.contributor.author | Jiang, P | - |
| dc.contributor.author | Katchasuwanmanee, K | - |
| dc.date.accessioned | 2020-10-09T11:04:42Z | - |
| dc.date.available | 2020-01-01 | - |
| dc.date.available | 2020-10-09T11:04:42Z | - |
| dc.date.issued | 2020-09-29 | - |
| dc.identifier.citation | Li, P., Cheng, K., Jiang, P. and Katchasuwanmanee, K. (2022) 'Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies', Journal of Intelligent Manufacturing, 33, pp. 103 - 119. doi: 10.1007/s10845-020-01646-2. | en_US |
| dc.identifier.issn | 0956-5515 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/21634 | - |
| dc.description.sponsorship | Natural Science Foundation of China, Grant Nos. 51975464 and 71571142. | en_US |
| dc.format.extent | 103 - 119 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.relation | Investigation on industrial dataspace -pulished-31-8-2020.pdf | - |
| dc.rights | This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Intelligent Manufacturing, following peer review. The final authenticated version is available online at https://doi.org/10.1007/s10845-020-01646-2. | - |
| dc.rights.uri | https://www.springernature.com/gp/open-research/policies/journal-policies | - |
| dc.subject | industrial dataspace | en_US |
| dc.subject | machining knowledge | en_US |
| dc.subject | machining operations control | en_US |
| dc.subject | knowledge representation | en_US |
| dc.subject | knowledge graph | en_US |
| dc.title | Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1007/s10845-020-01646-2 | - |
| dc.relation.isPartOf | Journal of Intelligent Manufacturing | - |
| pubs.publication-status | Published | - |
| pubs.volume | 33 | - |
| dc.identifier.eissn | 1572-8145 | - |
| dc.rights.holder | Springer Nature | - |
| Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Intelligent Manufacturing, following peer review. The final authenticated version is available online at https://doi.org/10.1007/s10845-020-01646-2. | 4.99 MB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.