Publication type: Conference paper
Type of review: Peer review (publication)
Title: End-to-end digital twin approach for near-real-time decision support services
Authors: Schweiger, Lukas
Meierhofer, Jürg
Barbieri, Cosimo
Rapaccini, Mario
et. al: No
DOI: 10.1007/978-3-030-97042-0_7
Proceedings: Smart services summit : smart services supporting the new normal
Editors of the parent work: West, Shaun
Meierhofer, Jürg
Mangla, Utpal
Page(s): 67
Pages to: 75
Conference details: Fourth Smart Services Summit, Zurich, 22 October 2021
Issue Date: 27-Apr-2022
Series: Progress in IS
Publisher / Ed. Institution: Springer
Publisher / Ed. Institution: Cham
ISBN: 978-3-030-97041-3
Language: English
Subjects: Product service system; Digital twin; Symbiotic simulation; Near-real-time decision making
Subject (DDC): 658.403: Decision making, information management
Abstract: An end-to-end approach for near-real-time decision support services constructed of different elements from the fields of digital twins, decision support systems, data analytics, symbiotic simulations, and product-service systems is proposed based on a literature review. Parts of the concept have been validated based on two practical cases in an earlier research project. The model presented combines elements of those existing approaches from the literature into a single end-to-end model. The resulting end-to-end model will be tested in an industrial context to support service decision-makers.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

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