dc.contributor.author |
Zhong, Runyang |
en |
dc.contributor.author |
Xu, Xun |
en |
dc.contributor.author |
Wang, LH |
en |
dc.contributor.editor |
Wang, L |
en |
dc.contributor.editor |
Fratini, L |
en |
dc.contributor.editor |
Shih, A |
en |
dc.coverage.spatial |
Los Angeles, USA |
en |
dc.date.accessioned |
2017-10-05T01:50:31Z |
en |
dc.date.issued |
2017 |
en |
dc.identifier.citation |
In Procedia Manufacturing: 45th SME North American Manufacturing Research Conference, NAMRC 45, LA, USA. Elsevier. 10: 1-14. 2017 |
en |
dc.identifier.issn |
2351-9789 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/35881 |
en |
dc.description.abstract |
Smart Factory is one of the critical components in Industry 4.0 which is our next industrial generation. This paper introduces an Internet of Things (IoT) -enabled Smart Factory Visibility and Traceability Platform (iVTP for short) to ultimately achieve real-time production visualization within a smart factory. iVTP uses IoT technology to identify various manufacturing objects. Specifically, radio frequency identification (RFID) devices are used for converting various resources into smart manufacturing objects (SMOs) and their interactions thus are able to real-time reflect the production operations and behaviors. By innovatively using a laser-scanner in the shopfloor, iVTP is able to real-time display the movements of various SMOs and twin the real-time RFID data to show their states. A Cloud-based system architecture which enables all the services packaged and deployed in a Cloud allows typical end-users to easily define their production logics, download useful services, and develop their customized services. Several demonstrative scenarios are presented to show how iVTP can facilitate the typical decision-making, production and logistics operations in a smart factory. |
en |
dc.description.uri |
http://www.sme.org/namrchistory/ |
en |
dc.publisher |
Elsevier |
en |
dc.relation.ispartof |
NAMRI/SME NAMRC 45, Forty-Fifth North American Manufacturing Research Conference |
en |
dc.relation.ispartofseries |
Procedia Manufacturing: 45th SME North American Manufacturing Research Conference, NAMRC 45, LA, USA |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from http://www.sherpa.ac.uk/romeo/issn/2351-9789/ |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
en |
dc.title |
IoT-enabled Smart Factory Visibility and Traceability using laser-scanners |
en |
dc.type |
Conference Item |
en |
dc.identifier.doi |
10.1016/j.promfg.2017.07.103 |
en |
pubs.begin-page |
1 |
en |
pubs.volume |
10 |
en |
dc.description.version |
VoR - Version of Record |
en |
dc.rights.holder |
Copyright: The authors |
en |
pubs.end-page |
14 |
en |
pubs.finish-date |
2017-06-08 |
en |
pubs.publication-status |
Published |
en |
pubs.start-date |
2017-06-04 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Proceedings |
en |
pubs.elements-id |
618625 |
en |
pubs.org-id |
Engineering |
en |
pubs.org-id |
Mechanical Engineering |
en |
pubs.record-created-at-source-date |
2017-03-26 |
en |