Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/73807
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorLee, CKM-
dc.creatorLv, Y-
dc.creatorNg, KKH-
dc.creatorHo, W-
dc.creatorChoy, KL-
dc.date.accessioned2018-03-29T07:15:23Z-
dc.date.available2018-03-29T07:15:23Z-
dc.identifier.issn0020-7543-
dc.identifier.urihttp://hdl.handle.net/10397/73807-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2017 Informa UK Limited, trading as Taylor & Francis Groupen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 27 Oct 2017 (Published online), available online: http://www.tandfonline.com/10.1080/00207543.2017.1394592.en_US
dc.subjectIndustry 4.0en_US
dc.subjectInternet of thingsen_US
dc.subjectLow–volume, high-mixen_US
dc.subjectSmart logisticsen_US
dc.subjectWarehouse management systemen_US
dc.titleDesign and application of Internet of things-based warehouse management system for smart logisticsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2753-
dc.identifier.epage2768-
dc.identifier.volume56-
dc.identifier.issue8-
dc.identifier.doi10.1080/00207543.2017.1394592-
dcterms.abstractWarehouse operations need to change due to the increasing complexity and variety of customer orders. The demand for real-time data and contextual information is requried because of the highly customised orders, which tend to be of small batch size but with high variety. Since the orders frequently change according to customer requirements, the synchronisation of purchase orders to support production to ensure on-time order fulfilment is of high importance. However, the inefficient and inaccurate order picking process has adverse effects on the order fulfilment. The objective of this paper is to propose an Internet of things (IoT)-based warehouse management system with an advanced data analytical approach using computational intelligence techniques to enable smart logistics for Industry 4.0. Based on the data collected from a case company, the proposed IoT-based WMS shows that the warehouse productivity, picking accuracy and efficiency can be improved and it is robust to order variability.-
dcterms.accessRightsopen access-
dcterms.bibliographicCitationInternational journal of production research, 2018, v. 56, no. 8, p. 2753-2768-
dcterms.isPartOfInternational journal of production research-
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85032352517-
dc.identifier.eissn1366-588X-
dc.identifier.rosgroupid2017001332-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201802 bcrc-
dc.description.oaAccepted Manuscript-
dc.identifier.FolderNumbera0768-n06-
dc.identifier.SubFormID1567-
dc.description.fundingSourceSelf-funded-
dc.description.pubStatusPublished-
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