Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105814
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorWu, CH-
dc.creatorNg, SCH-
dc.creatorKwok, KCM-
dc.creatorYung, KL-
dc.date.accessioned2024-04-23T04:31:31Z-
dc.date.available2024-04-23T04:31:31Z-
dc.identifier.urihttp://hdl.handle.net/10397/105814-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rightsCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wu C-H, Ng SC-H, Kwok KC-M, Yung K-L. Applying Industrial Internet of Things Analytics to Manufacturing. Machines. 2023; 11(4):448 is available at https://doi.org/10.3390/machines11040448.en_US
dc.subjectData-driven analyticsen_US
dc.subjectIdle timeen_US
dc.subjectIndustrial Internet of Thingsen_US
dc.subjectIndustry 4.0en_US
dc.subjectSmart factoryen_US
dc.titleApplying industrial internet of things analytics to manufacturingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume11-
dc.identifier.issue4-
dc.identifier.doi10.3390/machines11040448-
dcterms.abstractThe proliferation of Industry 4.0 (I4.0) technologies has created a new manufacturing landscape for manufacturing, requiring that companies follow I4.0 trends to stay competitive. However, in this novel digital automated environment, these companies must also ensure that lean manufacturing principles are upheld. This study proposes a data-driven framework for analysing raw data across machines in manufacturing systems that can provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework offers an alternative approach to improving manufacturing processes that involves utilising the power of I4.0 technologies in conjunction with lean manufacturing principles. This study’s examination of unprocessed data also provides guidance on improving legislation. The findings of this study provide direction for future research in the field of manufacturing and offer useful advice to businesses wishing to integrate I4.0 technologies into their operations.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMachines, Apr. 2023, v. 11, no. 4, 448-
dcterms.isPartOfMachines-
dcterms.issued2023-04-
dc.identifier.scopus2-s2.0-85156226433-
dc.identifier.eissn2075-1702-
dc.identifier.artn448-
dc.description.validate202404 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextSchool Research Granten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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