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End-to-End Digital Twin Approach for Near-Real-Time Decision Support Services

In: Smart Services Summit

Author

Listed:
  • Lukas Schweiger

    (Institute of Data Analysis and Process Design, Zuerich University of Applied Sciences)

  • Jürg Meierhofer

    (Institute of Data Analysis and Process Design, Zuerich University of Applied Sciences)

  • Cosimo Barbieri

    (Department of Industrial Engineering, Università degli Studi di Firenze)

  • Mario Rapaccini

    (Department of Industrial Engineering, Università degli Studi di Firenze)

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.

Suggested Citation

  • Lukas Schweiger & Jürg Meierhofer & Cosimo Barbieri & Mario Rapaccini, 2022. "End-to-End Digital Twin Approach for Near-Real-Time Decision Support Services," Progress in IS, in: Shaun West & Jürg Meierhofer & Utpal Mangla (ed.), Smart Services Summit, pages 67-75, Springer.
    • Handle: RePEc:spr:prochp:978-3-030-97042-0_7
    DOI: 10.1007/978-3-030-97042-0_7
    as

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