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Improving The Decision-Making Process By Modeling Digital Twins In A Big Data Environment

Author

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  • Madalina CUC

    (Mihai Viteazul National Intelligence Academy)

Abstract

Moving to the Industry 4.0 stage. will lead to process automation and implicitly to the change of classical decision support systems with some based on realtime evaluation of processes, on the processing of large and varied volumes of data, in continuous flow and at high speeds, all these elements converging towards automation decision. This involves the creation of virtual models faithful to physical processes and products, models obtained through specific BIG DATA processes. The purpose of this paper is to describe a framework for applying decision support based on the model of digital twins in a BIG DATA ecosystem, the description of the defining elements specific to the decision cycle, the modeling and implementation of this concept.

Suggested Citation

  • Madalina CUC, 2021. "Improving The Decision-Making Process By Modeling Digital Twins In A Big Data Environment," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(1), pages 138-154, May.
    • Handle: RePEc:aio:manmar:v:xix:y:2021:i:1:p:138-154
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    References listed on IDEAS

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    1. Kendrik Yan Hong Lim & Pai Zheng & Chun-Hsien Chen, 2020. "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1313-1337, August.
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    More about this item

    Keywords

    management; decision-making processes; BIG DATA; artificial intelligence; Digital Twins;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General

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