Production’s digital transformation analysis using Industry 4.0 technologies

  • Sergey V. Novikov Moscow Aviation Institute (National Research University), Moscow, Russia https://orcid.org/0000-0001-6921-1760
  • Andrey A. Sazonov Institute of Engineering Economics and Humanities, Moscow Aviation Institute (National Research University), Moscow, Russia.
Keywords: economic trends, Industry 4.0 technological components implementation, industry’s digital transformation, modern business models, production processes efficiency increase, production’s digital transformation, technological modernization.

Abstract

The article is devoted to a detailed analysis of the industry’s digital transformation processes based on the use of Industry 4.0 technologies. The theoretical analysis made it possible to establish that technological trends are often in the spotlight, however, the need for transformation is not posed by technology as such, but by deep shifts in the enterprise’s external environment caused by digitalization. The study of industry transformation global mechanisms allowed the article’s authors to identify eight key levers necessary for creating value due to the Industry 4.0 technologies implementation at a high-tech production. In conclusion, the authors consider the technological transformation process in Russia, as well as the main directions that can effectively accelerate it.

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Author Biographies

Sergey V. Novikov, Moscow Aviation Institute (National Research University), Moscow, Russia

PhD in Economics, Associate Professor, Moscow Aviation Institute (National Research University), Moscow, Russia

Andrey A. Sazonov, Institute of Engineering Economics and Humanities, Moscow Aviation Institute (National Research University), Moscow, Russia.

PhD in Economics, Associate Professor, Head of Institute of Engineering Economics and Humanities, Moscow Aviation Institute (National Research University), Moscow, Russia.

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Published
2020-03-21
How to Cite
Novikov, S., & Sazonov, A. (2020). Production’s digital transformation analysis using Industry 4.0 technologies. Amazonia Investiga, 9(27), 234-243. https://doi.org/10.34069/AI/2020.27.03.25
Section
Articles
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