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An architecture for IoT-enabled intelligent process-aware cloud production platform: a case study in a networked cloud clinical laboratory

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  • Mohammad Reza Rasouli

Abstract

Cloud production is an emerging paradigm that supports co-designing and co-producing integrated solutions with customers. The realisation of this paradigm requires integrated platforms that enable parties collaborating within a production ecosystem to inter-operate networked business processes. Previous research has proposed different architectures for cloud production platforms from different perspectives like virtualiseng and servitiseng manufacturing resources, distributed and networked sensing supported by IoT technologies, and service-oriented and process-centred computing to compose and enact networked production services. However, an integrated architecture that brings together insights from service-oriented cloud manufacturing, IoT-enabled intelligence, and networked process-centred service composition and enactment has not been sufficiently addressed in previous research. In order to incorporate insights from the mentioned different perspectives, in this paper architectural analysis, synthesis, and evaluation steps are conducted to propose a conceptual architecture for IoT-enabled intelligent process-aware cloud production platforms. This architecture describes design-time and run-time components of a cloud production platform that can sense and intelligently respond to events within a value network. To evaluate the applicability of the proposed architecture within real-life scenarios, a case study is conducted in a cloud clinical laboratory in Tehran, Iran. Within this case study, a concrete cloud clinical laboratory platform has been instantiated.

Suggested Citation

  • Mohammad Reza Rasouli, 2020. "An architecture for IoT-enabled intelligent process-aware cloud production platform: a case study in a networked cloud clinical laboratory," International Journal of Production Research, Taylor & Francis Journals, vol. 58(12), pages 3765-3780, June.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3765-3780
    DOI: 10.1080/00207543.2019.1634847
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    Cited by:

    1. Kurtz, Julian & Zinke-Wehlmann, Christian & Lugmair, Nina & Schymanietz, Martin & Roth, Angela, 2023. "Characterising smart service systems – Revealing the smart value," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 7(2), pages 112-128.

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