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Article: A Mechanised 3D Scanning Method for Item-level Radio Frequency Identification of Palletised Products

TitleA Mechanised 3D Scanning Method for Item-level Radio Frequency Identification of Palletised Products
Authors
Issue Date2015
PublisherElsevier. The Journal's web site is located at http://www.elsevier.com/locate/compind
Citation
Computers in Industry, 2015, v. 72, p. 36-46 How to Cite?
AbstractThe automatic, non-line-of-sight characteristics of radio frequency identification (RFID) technology for identifying multiple objects are conducive to full visibility and traceability of individual product items in a supply chain. However, practical implementation of item-level RFID-based applications necessitates solving some critical issues. Among these issues, reading tag data to identify a relatively large number of individual product items, which are usually packed in batches and distributed on pallets, is particularly a bottleneck, because it affects the accuracy and trustworthiness of batch distribution of products and all subsequent logistics operations in the supply chain. Current techniques for batch identification at item-level of palletised products suffer low reading rate and incomplete tag data acquisition, rendering the RFID systems unreliable. We address this issue by proposing a mechanised 3D scanning method for identification of tagged products in large numbers to facilitate supply chain management. The proposed method requires installing RFID readers only in the X-Y plane. The readers scan tagged products in the X and Y directions while the pallet is simultaneously rotated around to be effectively scanned in the Z direction. Different scanning patterns are adopted to alleviate the problems due to randomness of tag orientation and reader collisions. As such, 3D scanning of RFID tags for item-level applications is effectively achieved without incurring much hardware cost. The performance of the proposed method is validated using an RFID-enabled gate-door for identification of palletised apparel products with item-level RFID tagging. Experiment results show that the proposed method can achieve batch reading rates remarkably higher than those reported in literature. Moreover, a correlation between the batch reading rate and the batch density is established. Apparently, the proposed mechanised 3D scanning method for batch identification of item-level tagged product items can substantially enhance the accuracy and reliability of RFID-based supply chain management systems.
Persistent Identifierhttp://hdl.handle.net/10722/211768

 

DC FieldValueLanguage
dc.contributor.authorChoi, SH-
dc.contributor.authorYANG, B-
dc.contributor.authorCheung, HH-
dc.date.accessioned2015-07-21T02:10:20Z-
dc.date.available2015-07-21T02:10:20Z-
dc.date.issued2015-
dc.identifier.citationComputers in Industry, 2015, v. 72, p. 36-46-
dc.identifier.urihttp://hdl.handle.net/10722/211768-
dc.description.abstractThe automatic, non-line-of-sight characteristics of radio frequency identification (RFID) technology for identifying multiple objects are conducive to full visibility and traceability of individual product items in a supply chain. However, practical implementation of item-level RFID-based applications necessitates solving some critical issues. Among these issues, reading tag data to identify a relatively large number of individual product items, which are usually packed in batches and distributed on pallets, is particularly a bottleneck, because it affects the accuracy and trustworthiness of batch distribution of products and all subsequent logistics operations in the supply chain. Current techniques for batch identification at item-level of palletised products suffer low reading rate and incomplete tag data acquisition, rendering the RFID systems unreliable. We address this issue by proposing a mechanised 3D scanning method for identification of tagged products in large numbers to facilitate supply chain management. The proposed method requires installing RFID readers only in the X-Y plane. The readers scan tagged products in the X and Y directions while the pallet is simultaneously rotated around to be effectively scanned in the Z direction. Different scanning patterns are adopted to alleviate the problems due to randomness of tag orientation and reader collisions. As such, 3D scanning of RFID tags for item-level applications is effectively achieved without incurring much hardware cost. The performance of the proposed method is validated using an RFID-enabled gate-door for identification of palletised apparel products with item-level RFID tagging. Experiment results show that the proposed method can achieve batch reading rates remarkably higher than those reported in literature. Moreover, a correlation between the batch reading rate and the batch density is established. Apparently, the proposed mechanised 3D scanning method for batch identification of item-level tagged product items can substantially enhance the accuracy and reliability of RFID-based supply chain management systems.-
dc.languageeng-
dc.publisherElsevier. The Journal's web site is located at http://www.elsevier.com/locate/compind-
dc.relation.ispartofComputers in Industry-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in [Journal title]. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL#, ISSUE#, (DATE)] DOI#-
dc.titleA Mechanised 3D Scanning Method for Item-level Radio Frequency Identification of Palletised Products-
dc.typeArticle-
dc.identifier.emailChoi, SH: shchoi@hkucc.hku.hk-
dc.identifier.emailCheung, HH: hh.cheung@hku.hk-
dc.identifier.authorityChoi, SH=rp00109-
dc.identifier.doi10.1016/j.compind.2015.04.001-
dc.identifier.hkuros245269-
dc.identifier.volume72-
dc.identifier.issue2015-
dc.identifier.spage36-
dc.identifier.epage46-
dc.publisher.placeUSA-

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