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From digital to universal manufacturing

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  • Andrew Kusiak

Abstract

The transformation of the manufacturing industry over the last two decades has been largely inspired by data. Digitisation has made its mark in different areas of manufacturing, from digital materials and processes to data science in decision-making. The digital manufacturing is evolving towards universal manufacturing that is highlighted in this paper. Different manufacturing initiatives are benchmarked and their relationship to universal manufacturing is demonstrated. The representation of enterprises in the universal manufacturing cloud is discussed. Product- and process-based specifications of digital enterprises are defined. Using these specifications, the enterprise configuration algorithm proposed in the paper is applied for the selection of component models. Two different representations, a node–node and an input–output matrix, of the digital component models are considered. The extended topological sorting algorithm is applied to construct an integrated digital model.

Suggested Citation

  • Andrew Kusiak, 2022. "From digital to universal manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 60(1), pages 349-360, January.
  • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:1:p:349-360
    DOI: 10.1080/00207543.2021.1948137
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    Cited by:

    1. Andrew Kusiak, 2024. "Hyper-automation in manufacturing industry," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 1-2, January.
    2. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    3. Ibrahim Yitmen & Amjad Almusaed & Sepehr Alizadehsalehi, 2023. "Investigating the Causal Relationships among Enablers of the Construction 5.0 Paradigm: Integration of Operator 5.0 and Society 5.0 with Human-Centricity, Sustainability, and Resilience," Sustainability, MDPI, vol. 15(11), pages 1-25, June.

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