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Design of smart connected manufacturing resources to enable changeability, reconfigurability and total-cost-of-ownership models in the factory-of-the-future

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  • Stelian Brad
  • Mircea Murar
  • Emilia Brad

Abstract

The fourth industrial revolution requires higher capabilities of changeability and reconfigurability (C–R) of the future factories (FoF), as well as a higher focus on business models that are based on total-cost-of-ownership (TCO) paradigm. Up to date, there are little scientific contributions to deploy C–R into TCO models, as well as to systematic plan and design manufacturing resources such as to facilitate FoF ecosystem. In order to address this issue, this paper introduces research results that show how to deploy C–R, connectivity, smartness and TCO requirements into the technical solutions of manufacturing resources of FoF. Contributions emerging from this research include an index to measure C–R capability of manufacturing resources, a model to assess economic feasibility of a FoF over its lifecycle, as well as a methodology and related tools to design smart connected manufacturing resources with embedded features to facilitate changeability and reconfigurability in a FoF. Theoretical contributions are explained through a case study of a fast reconfigurable robotic manufacturing cell. Preliminary results demonstrate that it is possible to rapid design smart connected manufacturing resources and integrate them into FoF architectures that support convertibility, integrability, modifiability, adaptability, serviceability, scalability, integration of resources from various producers, service clustering and cloud-based services.

Suggested Citation

  • Stelian Brad & Mircea Murar & Emilia Brad, 2018. "Design of smart connected manufacturing resources to enable changeability, reconfigurability and total-cost-of-ownership models in the factory-of-the-future," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2269-2291, March.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:6:p:2269-2291
    DOI: 10.1080/00207543.2017.1400705
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    Cited by:

    1. Silvestro Vespoli & Guido Guizzi & Elisa Gebennini & Andrea Grassi, 2022. "A novel throughput control algorithm for semi-heterarchical industry 4.0 architecture," Annals of Operations Research, Springer, vol. 310(1), pages 201-221, March.
    2. Calabrese, Armando & Costa, Roberta & Tiburzi, Luigi & Brem, Alexander, 2023. "Merging two revolutions: A human-artificial intelligence method to study how sustainability and Industry 4.0 are intertwined," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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