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Conference Paper: Analytical target cascading for optimal configuration of production service systems

TitleAnalytical target cascading for optimal configuration of production service systems
Authors
KeywordsAnalytical target cascading
Product service system (PSS)
Manufacturing alliance
Virtual manufacturing
Extended enterprise
Issue Date2010
PublisherSpringer-Verlag.
Citation
The 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 1627-1646 How to Cite?
AbstractProduct Service System (PSS) advocates an innovative business mode where manufacturers provide products in the form of services instead of mere entity offerings. This mode not only enhances the utilization rate of products and resources, but also improves the service levels throughout the whole product lifecycle. PSS extension to manufacturing environment results in Production Service System (PnSS), which forms a hierarchically organized service-oriented manufacturing alliance composed of manufacturers/suppliers with various production service capabilities to collaborate a customer order. The process of selecting the optimal production service providers for a PnSS is called Production Service System Configuration (PnSSC). It is difficult to apply a centralized optimization method for a PnSSC problem because the members participating into the PnSS are uncertain while most of them are not willing to submit their decision details to the centralized decision model. This paper therefore proposes an Analytical Target Cascading (ATC) based distributed configuration system, atcPortal, for PnSSC. Each service provider models their production capabilities as a web service hosted at local end while published at atcPortal, while the embedded ATC mechanism will coordinate all the related services to formulate the optimal PnSSC for a given customer order. This distributed optimization system avoids centralized modeling and optimization process and thus protects enterprise privacy.
Persistent Identifierhttp://hdl.handle.net/10722/126229

 

DC FieldValueLanguage
dc.contributor.authorQu, Ten_HK
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorZhang, YFen_HK
dc.contributor.authorYang, HDen_HK
dc.date.accessioned2010-10-31T12:16:52Z-
dc.date.available2010-10-31T12:16:52Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 1627-1646en_HK
dc.identifier.urihttp://hdl.handle.net/10722/126229-
dc.description.abstractProduct Service System (PSS) advocates an innovative business mode where manufacturers provide products in the form of services instead of mere entity offerings. This mode not only enhances the utilization rate of products and resources, but also improves the service levels throughout the whole product lifecycle. PSS extension to manufacturing environment results in Production Service System (PnSS), which forms a hierarchically organized service-oriented manufacturing alliance composed of manufacturers/suppliers with various production service capabilities to collaborate a customer order. The process of selecting the optimal production service providers for a PnSS is called Production Service System Configuration (PnSSC). It is difficult to apply a centralized optimization method for a PnSSC problem because the members participating into the PnSS are uncertain while most of them are not willing to submit their decision details to the centralized decision model. This paper therefore proposes an Analytical Target Cascading (ATC) based distributed configuration system, atcPortal, for PnSSC. Each service provider models their production capabilities as a web service hosted at local end while published at atcPortal, while the embedded ATC mechanism will coordinate all the related services to formulate the optimal PnSSC for a given customer order. This distributed optimization system avoids centralized modeling and optimization process and thus protects enterprise privacy.-
dc.languageengen_HK
dc.publisherSpringer-Verlag.-
dc.relation.ispartofProceedings of the 6th CIRP-Sponsored International Conference on Digital Enterprise Technology-
dc.subjectAnalytical target cascading-
dc.subjectProduct service system (PSS)-
dc.subjectManufacturing alliance-
dc.subjectVirtual manufacturing-
dc.subjectExtended enterprise-
dc.titleAnalytical target cascading for optimal configuration of production service systemsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailQu, T: quting@hku.hken_HK
dc.identifier.emailHuang, GQ: gqhuang@hkucc.hku.hken_HK
dc.identifier.emailZhang, YF: xjtuzyf@hku.hken_HK
dc.identifier.emailYang, HD: yanghd@yeah.neten_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1007/978-3-642-10430-5_122-
dc.identifier.hkuros175692en_HK
dc.identifier.volume66-
dc.identifier.spage1627-
dc.identifier.epage1646-
dc.description.otherThe 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 1627-1646-

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