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Analysis of Digital Transformation of Quality Management Processes

https://doi.org/10.35596/1729-7648-2026-32-3-62-70

Abstract

In the context of the digital transformation of industry, quality management is faced with the need to revise traditional approaches based on sampling and statistical methods in favor of proactive and predictive models integrated into the enterprise's digital environment. However, the literature lacks a systematic analysis of quality management processes in terms of their suitability for digital transformation, which complicates the selection of effective strategies for implementing intelligent tools. The scientific novelty of this study lies in the systematization of key quality management processes, the identification of key barriers hindering digitalization, and the determination of factors influencing the suitability of processes for automation. Of particular interest is the analysis of the influence of the human factor, problems of integrating heterogeneous information systems, and limitations associated with the formalization of analytical processes on the effectiveness of digital transformation. The author's arguments favor a systems approach to digitalization, which involves preliminary analysis and adjustment of existing processes, phased implementation with an emphasis on management processes, and the development of personnel competencies as a prerequisite for success. The obtained results can be used by managers and quality specialists when planning digital transformation projects at industrial enterprises.

About the Author

M. Tikhonov
National Research University of Electronic Technology, Moscow
Russian Federation

Tikhonov M., Cand. Sci. (Tech.), Associate Professor, Associate Professor at the Institute of Systems and Software Engineering and Information Technology



References

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Review

For citations:


Tikhonov M. Analysis of Digital Transformation of Quality Management Processes. Digital Transformation. 2026;32(3):62-70. (In Russ.) https://doi.org/10.35596/1729-7648-2026-32-3-62-70

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ISSN 2522-9613 (Print)
ISSN 2524-2822 (Online)