Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104418
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorCheng, Yen_US
dc.creatorXie, Yen_US
dc.creatorZhao, Den_US
dc.creatorJi, Pen_US
dc.creatorTao, Fen_US
dc.date.accessioned2024-02-05T08:49:42Z-
dc.date.available2024-02-05T08:49:42Z-
dc.identifier.issn2168-2216en_US
dc.identifier.urihttp://hdl.handle.net/10397/104418-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Cheng, Y., Xie, Y., Zhao, D., Ji, P., & Tao, F. (2020). Scalable Hypernetwork-Based Manufacturing Services Supply Demand Matching Toward Industrial Internet Platforms. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(12), 5000–5014 is available at https://doi.org/10.1109/TSMC.2019.2944524.en_US
dc.subjectCross-enterprise collaborationen_US
dc.subjectHypernetworken_US
dc.subjectIndustrial Internet platformen_US
dc.subjectManufacturing service (MS)en_US
dc.subjectScalabilityen_US
dc.subjectSupply demand matching (SDM)en_US
dc.titleScalable hypernetwork-based manufacturing services supply demand matching toward industrial internet platformsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage5000en_US
dc.identifier.epage5014en_US
dc.identifier.volume50en_US
dc.identifier.issue12en_US
dc.identifier.doi10.1109/TSMC.2019.2944524en_US
dcterms.abstractWith the deeper application of sensor & cloud-based environment into manufacturing, deploying the industrial Internet platforms toward smart manufacturing has been more concerned. Based on the platforms, ubiquitous enterprises could participate in and support cross-enterprise collaboration, so that their distributed manufacturing facilities and capabilities could be shared and utilized in the form of manufacturing services (MSs). However, in order to achieve the successful application of the platforms, how to settle the supply demand matching (SDM) of the distributed manufacturing facilities and capabilities in the form of MSs, namely, MSs-SDM, becomes one of the most urgent problems to be solved. In addition, the trend of manufacturing socialization makes this problem much more scalable. In this context, this article aims to establish a set of hypernetwork-based models for the scalable MSs-SDM problem at first. An enterprises collaborative network is derived which is the projection of the underlying MSs-SDM situation to the upper-layer enterprises. Second, a method according to the evaluation on the cross-enterprise collaboration is proposed for this problem. In which, the created utilities, the rates of service invocation, and task allocation from both the global view of the overall network and the local view of each participated enterprise are evaluated. Finally, two steps of experiments introducing scalabilities illustrate the feasibility of the proposed models and the effectiveness of the derived method for MSs-SDM optimization, and further reveal five managerial implications to improve the operation and industrial practice of the platforms.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on systems, man, and cybernetics. Systems, Dec. 2020, v. 50, no. 12, p. 5000-5014en_US
dcterms.isPartOfIEEE transactions on systems, man, and cybernetics. Systemsen_US
dcterms.issued2020-12-
dc.identifier.scopus2-s2.0-85096654578-
dc.identifier.eissn2168-2232en_US
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0407-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS23625536-
dc.description.oaCategoryGreen (AAM)en_US
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