Issues of functioning of information systems for increasing productivity of technological cycles in various industries

L.S. Zvyagin

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Abstract: The article presents a comprehensive analysis of the application of modern information and measuring systems (IMS) as a tool for improving the efficiency and reliability of technological processes in the context of “Industry 4.0”. The architecture, components and principles of IMS operation are considered, including their integration with the Industrial Internet of Things (IIoT), big data and artificial intelligence. Based on the analysis of specific examples from leading Russian industries, such as oil and gas, mechanical engineering, energy, chemical and metallurgical, the significant impact of IMS on resource optimization, increased productivity and security is demonstrated. The article proposes a new integrated multi-level adaptive scheme for using IMS, which combines the physical, control, production and corporate levels into a single system with an analytical core based on artificial intelligence. The developed scheme ensures proactive decision-making and the creation of self-regulating production cycles.
Conclusions. The results of the study confirm that the implementation of the IIS helps to move to predictive maintenance and improve product quality. The article summarizes the existing experience and identifies promising areas for the development of the IIS for building sustainable and competitive industrial enterprises.

Keywords: information and measuring system, technological process, efficiency, reliability, industrial automation, Industry 4.0, SCADA, MES, predictive maintenance, Industrial Internet of Things (IIoT)

For citation. Zvyagin L.S. Issues of functioning of information systems for increasing productivity of technological cycles in various industries. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 6. Pp. 157–171. DOI: 10.35330/1991-6639-2025-27-6-157-171

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Information about the author

Leonid S. Zvyagin, Candidate of Economics, Associate Professor, Financial University under the Government of the Russian Federation;
49/2, Leningradsky Prospect, Moscow, 125167, Russia;
lszvyagin@fa.ru, ORCID: https://orcid.org/0000-0003-4983-6012, SPIN-code: 9400-1926