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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23656
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dc.contributor.authorMeierhofer, Jürg-
dc.contributor.authorSchweiger, Lukas-
dc.contributor.authorLu, Jinzhi-
dc.contributor.authorZüst, Simon-
dc.contributor.authorWest, Shaun-
dc.contributor.authorStoll, Oliver-
dc.contributor.authorKiritsis, Dimitris-
dc.date.accessioned2021-12-08T15:17:05Z-
dc.date.available2021-12-08T15:17:05Z-
dc.date.issued2021-
dc.identifier.issn2076-3417de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/23656-
dc.description.abstractThe goal of this paper is to further elaborate a new concept for value creation by decision support services in industrial service ecosystems using digital twins and to apply it to an extended case study. The aim of the original model was to design and integrate an architecture of digital twins derived from business needs that leveraged the potential of the synergies in the ecosystem. The conceptual framework presented in this paper extends the semantic ontology model for integrating the digital twins. For the original model, technical modeling approaches were developed and integrated into an ecosystem perspective based on a modeling of the ecosystem and the actors’ decision jobs. In a service ecosystem comprising several enterprises and a multitude of actors, decision making is based on the interlinkage of the digital twins of the equipment and the processes, which is achieved by the semantic ontology model further elaborated in this paper. The implementation of the digital twin architecture is shown in the example of a manufacturing SME (small and medium-sized enterprise) case that was introduced in. The mixed semantic modeling and model-based systems engineering for this implementation is discussed in further detail in this paper. The findings of this detailed study provide a theoretical concept for implementing digital twins on the level of service ecosystems and integrating digital twins based on a unified ontology. This provides a practical blueprint to companies for developing digital twin based services in their own operations and beyond in their ecosystem.de_CH
dc.language.isoende_CH
dc.publisherMDPIde_CH
dc.relation.ispartofApplied Sciencesde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectDigital twinde_CH
dc.subjectSmart servicede_CH
dc.subjectData modelingde_CH
dc.subjectDecision supportde_CH
dc.subjectSimulationde_CH
dc.subjectSemantic modelingde_CH
dc.subject.ddc658.5: Produktionssteuerungde_CH
dc.titleDigital twin-enabled decision support services in industrial ecosystemsde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.3390/app112311418de_CH
dc.identifier.doi10.21256/zhaw-23656-
zhaw.funding.euNode_CH
zhaw.issue23de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start11418de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume11de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedDIZH Fellowshipde_CH
zhaw.webfeedIndustrie 4.0de_CH
zhaw.webfeedMEM-Industriede_CH
zhaw.webfeedService Engineeringde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.funding.zhawDigital-Twin-basierte Dienstleistungen zur Unterstützung der Entscheidungsfindung entlang des Produktlebenszyklus von Investitionsgüternde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.monitoring.costperiod2021de_CH
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Meierhofer, J., Schweiger, L., Lu, J., Züst, S., West, S., Stoll, O., & Kiritsis, D. (2021). Digital twin-enabled decision support services in industrial ecosystems. Applied Sciences, 11(23), 11418. https://doi.org/10.3390/app112311418
Meierhofer, J. et al. (2021) ‘Digital twin-enabled decision support services in industrial ecosystems’, Applied Sciences, 11(23), p. 11418. Available at: https://doi.org/10.3390/app112311418.
J. Meierhofer et al., “Digital twin-enabled decision support services in industrial ecosystems,” Applied Sciences, vol. 11, no. 23, p. 11418, 2021, doi: 10.3390/app112311418.
MEIERHOFER, Jürg, Lukas SCHWEIGER, Jinzhi LU, Simon ZÜST, Shaun WEST, Oliver STOLL und Dimitris KIRITSIS, 2021. Digital twin-enabled decision support services in industrial ecosystems. Applied Sciences. 2021. Bd. 11, Nr. 23, S. 11418. DOI 10.3390/app112311418
Meierhofer, Jürg, Lukas Schweiger, Jinzhi Lu, Simon Züst, Shaun West, Oliver Stoll, and Dimitris Kiritsis. 2021. “Digital Twin-Enabled Decision Support Services in Industrial Ecosystems.” Applied Sciences 11 (23): 11418. https://doi.org/10.3390/app112311418.
Meierhofer, Jürg, et al. “Digital Twin-Enabled Decision Support Services in Industrial Ecosystems.” Applied Sciences, vol. 11, no. 23, 2021, p. 11418, https://doi.org/10.3390/app112311418.


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