KSHP. OMD №5-2025 el.dop

I. S. Maksimov, S. A. Galanskiy (Volga State University of Railway Transport, Samara) 

Determination of the allowance distribution during mortise grinding of external shaped surfaces

The article explores a new method of grinding the outer shaped surfaces of rotating parts. When developing this method, special attention is paid to the formation of a complex profile, which is essential for achieving high precision and component processing qualities. Mortise grinding using circles with an intermittent working surface opens up new possibilities for improving the technological process of grinding external shaped surfaces. When forming a complex profile, not only the geometry of the grinding wheel plays a key role, but also the features of the interaction of the wheel with the processed material. The intermittent working surface of the grinding wheel can significantly improve the grinding process, providing better heat dissipation and reducing the likelihood of the wheel getting dirty. This, in turn, contributes to a more stable grinding process and improved quality of the final product. Analysis of the wear mechanism of grinding wheels shows that it occurs under the influence of various factors, including the abrasive properties of the processed material, feed rate and grinding modes. As a result, the research of a new method of grinding external shaped surfaces not only opens up new prospects for improving productivity, but also contributes to a deeper understanding of the processes occurring during the machining of complex shapes. This is undoubtedly of great importance for both researchers and practitioners in the field of mechanical engineering.
Keywords: mortise grinding; shaped surface; allowance for the processed profile; radial wear of the abrasive wheel.

 

A. S. Govorkov, N. V. Podrez, T. V. Bozheeva (Irkutsk National Research Technical University, Irkutsk)

Accounting of technological data of the enterprise in the production of new types of products

Recently, many enterprises of our country related to the aerospace complex, defense industry, heavy engineering have begun to produce new types of products that are necessary for wide application in various industries, and are also in high demand in other countries. The production of new parts in the aviation and space industry is associated with significant difficulties associated with the re-equipment of production, the development of new technologies and the selection of materials. These difficulties can significantly affect the possibility of implementing new projects. In order to effectively organize the design process, it is necessary to use specialized methods and techniques that will save the enterprise's funds and reduce the time of both the design stage and the process of manufacturing the part.
Keywords: detail; unit; process; product; expert evaluation method.

 

T. I. Petrov (Kazan State Power Engineering University, Kazan)

Improving the energy efficiency of synchronous motors through multi-purpose optimization of magnetic systems and reducing parasitic losses in stator windings

The problem of increasing the energy efficiency of synchronous motors is particularly relevant in the context of modern environmental and economic challenges. The present study is aimed at developing a comprehensive approach to optimizing the energy characteristics of synchronous motors by improving their magnetic systems and minimizing parasitic losses in the stator windings. The methodological base of the study includes multiparameter computer modeling of magnetic fields, finite element analysis of thermal processes, experimental tests on specialized stands and statistical processing of the results. The empirical basis of the work was experimental data obtained during tests of a series of industrial synchronous motors with a power of 75 to 315 kW in various operating modes. As a result of the study, a multi-criteria technique for optimizing the geometry of the magnetic circuit is proposed, taking into account the saturation and nonlinearity of the magnetic characteristics, which allows reducing losses in steel by 12–15 %. A new configuration of stator windings with an optimized pitch has been developed, providing a decrease in additional losses by 18,7 %. The optimal parameters of magnetic circuit segmentation are determined, reducing eddy current losses by 23,4 % while maintaining the mechanical strength of the structure. A correlation is established between the parameters of magnetic system materials and the energy characteristics of the engine, allowing us to predict the efficiency of using new electrical steels. The theoretical significance of the work lies in the development of a methodology for multi-purpose optimization of electrical machines, and the practical value is determined by the possibility of implementing the obtained results in the production of modern energy-efficient synchronous motors with an efficiency rating of up to 96,8 %.
Keywords: synchronous motors; energy efficiency; magnetic systems; parasitic losses; multi-objective optimization; stator windings; mathematical modeling.

 

N. K. Skvortsova, E. G. Matys (Industrial University of Tyumen, Tyumen)

Optimization of the cost structure for industrial production

An approach to optimization of the cost structure for industrial production is considered. A model for optimization of the cost structure by cost elements is proposed as one of the areas for improving the efficiency of an enterprise.
Keywords: cost of industrial production; optimization of the cost structure; cost composition; factor analysis; optimization criteria; cost management.

 

I. V. Klaptyuk, Yu. N. Belshina (Saint-Petersburg university of State fire service of EMERCOM of Russia, Saint-Petersburg)

Solving identification problems in the study of anti-corrosion and fire-protective coatings for metal structures

The article demonstrates the capabilities of infrared spectroscopy in solving the problems of identifying anticorrosive and fire-protective paint and varnish coatings used to protect metal structures at industrial facilities. In the course of the study, the spectral characteristics of various inorganic fillers and pigments, as well as additives that provide swelling of intumescent fire-protective coatings, were studied and systematized. An analytical scheme for identification was developed, including the parallel use of various methods for sample preparation of the samples under study with subsequent analysis of the obtained spectral data.
Keywords: paint and varnish coatings; anti-corrosion coatings; fire-protective coatings; metal structures; infrared spectroscopy; identification.

 

N. L. Udaltsova (Financial University under the Government of the Russian Federation, Russia, Moscow)

Implementation of blockchain platforms for life cycle management of metallurgical products in distributed project teams

The modern metallurgical industry faces significant challenges associated with the need to increase process transparency, end-to-end product tracking and optimize the interaction of production chain participants. This study is focused on a comprehensive analysis of the possibilities of integrating blockchain technologies into the life cycle management system of metallurgical products when working with geographically distributed project teams. Based on data from 17 metallurgical enterprises, a study was conducted on the effectiveness of implementing private blockchain platforms to solve product traceability problems, automate business processes and create a single trusted information space. A multi-level methodology was developed for assessing the economic and technological effects of implementing blockchain solutions in the metallurgical sector. It was found that the integration of blockchain infrastructure into existing information systems allows for a 37,4 % increase in the speed of tracking industrial batches, a 42,8 % reduction in the time of interfunctional documentation approval and a 18,6 % reduction in transaction costs when interacting with counterparties. The critical factors for the successful implementation of blockchain platforms in metallurgy are identified: consensus model, distributed ledger architecture, integration with existing ERP systems, access rights management and standardization of data exchange protocols. The results obtained demonstrate the potential of blockchain technologies for transforming the processes of managing the life cycle of metallurgical products and forming new models of industry interaction in the context of the digital economy.
Keywords: blockchain technologies; metallurgical industry; product lifecycle management; distributed project teams; digital transformation; traceability; smart contracts.

 

N. V. Kuchkovskaya (Financial University under the Government of the Russian Federation, Moscow)

Prospects for using digital models and artificial intelligence to automate and robotize production processes at industrial enterprises of the future

The article analyzes the prospects for using digital models and artificial intelligence (AI) to automate and robotize production processes at industrial enterprises. Based on a conceptual review of the literature and terminology analysis, key trends and unresolved issues in this area are identified. The relevance of developing new approaches to integrating AI into production is substantiated, taking into account the specifics of enterprise digitalization. Methods of system analysis, statistical data processing, and expert assessment are used. The empirical base consists of data on the implementation of AI at 120 enterprises in various industries. It has been established that AI can increase labor productivity by 15–20 %, reduce energy costs by 10–12 %, and minimize losses from defects by 25–30 %. At the same time, only 10 % of enterprises have comprehensive digital transformation strategies. The need to develop a methodology for designing «smart factories» based on AI principles is substantiated. Priority areas for further research are outlined. The obtained results are important for the development of the theory of production organization in the context of Industry 4.0 and can be used in the creation of digital twins of enterprises.
Keywords: artificial intelligence; digital modeling; robotization of production; automation; Industry 4.0; digital twins.

 

I. H. Utakaeva (Financial University under the Government of the Russian Federation, Moscow)

Mathematical modeling of energy consumption of large industrial complexes using neural network algorithms and optimization graphs

This study is devoted to the development and testing of a comprehensive mathematical model for forecasting and optimizing energy consumption of industrial facilities based on the integration of neural network algorithms and optimization graph theory. The paper presents a critical analysis of existing approaches to energy consumption modeling and identifies their limitations when working with multiparameter dynamic systems. The proposed hybrid model is based on the synergy of recurrent neural networks with long short-term memory (LSTM) and optimization graphs with multivariate weighting functions, which allows taking into account nonlinear dependencies between production cycles, seasonal load and climatic factors. Empirical verification of the model was carried out on the data of 17 large industrial complexes in the metallurgical and petrochemical sectors for the period 2018–2023. The results demonstrate an increase in the accuracy of energy consumption forecasting by 18,7 % compared to traditional methods and a decrease in the root mean square error to 3,2 % with a forecast horizon of 30 days. The optimization component of the model ensured a reduction in excess energy consumption by 12,4–15,8 % while maintaining production indicators. The practical significance of the study is determined by the possibility of integrating the developed algorithms into existing energy management systems of industrial enterprises, which contributes to increased energy efficiency and a reduction in the carbon footprint. The theoretical value of the work lies in the development of a methodology for multimodal modeling of complex energy systems with a high degree of uncertainty and a large number of interdependent variables.
Keywords: energy modeling; neural network algorithms; optimization graphs; industrial energy efficiency; predictive analytics; multimodal models; energy management.

 

G. A. Gareeva (Kazan National Research Technical University named after A. N. Tupolev - KAI, Naberezhnye Chelny); D. R. Grigorieva, G. R. Arslanova (Kazan (Volga Region) Federal University, Naberezhnye Chelny Institute, Naberezhnye Chelny); I. I. Frolova (Kazan Innovative University named after V. G. Timiryasov, Naberezhnye Chelny); N. R. Zakirova (Naberezhnye Chelny State Pedagogical University, Naberezhnye Chelny) 

Effective order management and optimization of delivery service

The article presents the process of developing a database for a delivery service that provides centralized storage of information about orders, clients and couriers, automation of order processing and delivery status tracking, as well as the ability to analyze data to optimize business processes.
Keywords: delivery service; database; PostgreSQL; DBeaver; automation; data management; efficiency; optimization; relational model; customer accounting; order processing; order management.

 

N. V. Kuchkovskaya (Financial University under the Government of the Russian Federation, Moscow)

Optimizing investment decisions in heavy industries through the integration of predictive analytics and machine learning

Modern heavy industry operates in conditions of high market volatility and increasing complexity of investment decisions, which actualizes the need to develop comprehensive methodological approaches to optimizing capital investments. This study is aimed at creating an integrated model for making investment decisions based on the convergence of predictive analytics and machine learning algorithms adapted to the specifics of heavy industry. The empirical base of the study was data from 78 industrial enterprises in the metallurgical, mechanical engineering and petrochemical sectors for the period 2018–2023, including 2340 investment projects of various scales. The methodological tools of the study are based on multi-level analysis using gradient boosting algorithms, deep neural networks and Bayesian optimization in modeling the investment process. The results of the study demonstrate that the integration of predictive analytics into the investment process increases the accuracy of forecasting project profitability by 27,3 % (p < 0,01) and reduces the variance of the forecast error by 34,6 %. The developed dynamic model for optimizing the investment project portfolio, taking into account industry cyclicality and macroeconomic fluctuations, ensures an increase in the total return on investment by 8,4–11,2 percentage points. Practical implementation of the proposed methodology in the form of an intelligent decision support system allows reducing capital expenditures by 15,7 % while maintaining target performance indicators. The results of the study expand the theoretical discourse in the field of investment management and form a methodological platform for further digitalization of management processes in heavy industry.
Keywords: predictive analytics; machine learning; investment optimization; heavy industry; intelligent decision-making systems; technological modernization; industrial economics.

 

S. A. Tronin (Financial University under the Government of the Russian Federation, Moscow)

Strategic management of industrial enterprises using data center technologies and distributed data storage in the context of the digital economy

The article considers the problem of strategic management of industrial enterprises in the digital economy. Particular attention is paid to the use of data center technologies and distributed data storage. Based on the literature analysis, key trends and gaps in research on this topic are identified. The author's terminology and conceptual model of strategic management are proposed, taking into account the specifics of the digital transformation of industry. The empirical base consists of data on 120 enterprises of various industries. Using statistical analysis methods and expert assessments, hypotheses about the impact of data centers and distributed storage on the effectiveness of strategic management are tested. A significant positive relationship between the level of implementation of these technologies and key performance indicators of enterprises (ROA, ROE, ROS) is revealed. The obtained results contribute to the development of the theory of strategic management and are of practical value for optimizing management processes in the context of Industry 4.0. Prospects for further interdisciplinary research at the intersection of management, computer science and engineering are outlined.
Keywords: strategic management; industrial enterprises; digital economy; data centers; distributed data storage; Industry 4.0.

 

V. P. Chasovskikh, E. V. Koch (Ural State University of Economics, Yekaterinburg)

Artificial intelligence technologies for the progress of technological and production operations of Russian enterprises

The study analyzes in detail the fundamental elements of digitalization, with a special focus on the functionality of artificial intelligence (AI) in this context. Innovative technologies in the field of AI that contribute to the expansion of technological and production horizons of enterprises are highlighted. The contribution of generative AI and its capabilities in project activities are examined. These methods are aimed at improving operational efficiency through automation, cost optimization and acceleration of production processes. In describing the results of the analysis of artificial intelligence, the article highlights the key components necessary for its operation, including infrastructure, procedures and tools for data processing and software development. A comparative analysis is carried out between traditional neural networks and new developments of the Kolmogorov-Arnold network. It is argued that the choice of a computer for artificial intelligence is the main and determining factor for the operation of an artificial intelligence system. The properties of Kolmogorov-Arnold networks are studied. Prospects for the use of AI in project management are systematized in accordance with the main thematic areas. The paper analyzes the influence of various factors on the level of AI development, with an emphasis on the latest microcircuits and artificial neural networks such as KAN. A model for assessing AI systems is formed, including unique metrics.
Keywords: technologies; AI; generative intelligence; microcircuits; machine learning; KAN neural networks. 

 

L. K. Babayan (Financial University under the Government of the Russian Federation, Moscow)

Prospects for the development of the electronics industry in order to achieve technological leadership

The article examines the development prospects of the Russian electronics industry as a key factor in achieving technological leadership, as defined by the Decree of the President of the Russian Federation dated 07.05.2024 No. 309. The author analyzes the strategic goals of the industry, including ensuring technological independence, developing microelectronics and integrating with high-tech sectors of the economy. Based on the PEST analysis, political, economic, social and technological factors influencing the industry, as well as key challenges are identified: sanctions pressure, dependence on imports, personnel shortage and lagging behind in production technologies. The author emphasizes the need to develop closed production cycles, specialized areas (radio photonics, neuromorphic processors) and strengthen cooperation with friendly countries. The low share of the industry in GDP, limited domestic demand and lack of investment in R&D are identified as limiting factors. To overcome these limitations, measures are proposed to modernize personnel training, create research and production consortiums and increase government support. 
Keywords: electronic industry; technological leadership; microelectronics; national projects; electronic industry strategy.

 

E. I. Moskvitina (Financial University under the Government of the Russian Federation, Moscow)

Evaluation of the possibilities of using successful global practices in the management of available technologies (BAT) in industry in Russia

The need to ensure sustainable development of Russian industry in the conditions of geopolitical and socio-economic "turbulence" determines the relevance of assessing the potential for using successful foreign practices in the country to manage the best available technologies (hereinafter referred to as BAT). Based on the analysis of Russian and foreign scientific research and expert and analytical materials over the past 5 years, it has been established that there remains a high interest in the issues of BAT application in industry. At the same time, modern studies do not pay enough attention to management tools for stimulating the use of BAT by industrial enterprises, in connection with which the key tools of state management of BAT in the European Union, the USA, China and Japan were systematized in the work. Based on the results of a comparative analysis of foreign and domestic experience, recommendations were developed and systematized for the Russian Federation in five key areas, including taking into account the industry and regional specifics of BAT in regulatory legal acts and reference documents, stimulating the growth of motivation of enterprises to use BAT, etc.
Keywords: best available technologies; sustainable development; industry; public administration; foreign experience.

 

P. I. Chuvakhin (Financial University under the Government of the Russian Federation, Moscow)

Comparative analysis of the risks of investing in traditional and digitalized industrial enterprises using cognitive technologies

The study is devoted to a comparative analysis of the risks of investing in traditional and digitalized industrial enterprises using cognitive technologies. In the context of the fourth industrial revolution, the transformation of production systems is becoming a prerequisite for maintaining competitiveness, but investment decisions in this area are associated with a high level of uncertainty. The work is based on an integrated methodological approach that combines quantitative and qualitative research methods: multivariate analysis of investment risks, cognitive modeling, expert assessments and scenario analysis. The empirical base consisted of data on 127 industrial enterprises of Russia and the EAEU countries for the period 2019–2023, which are at different stages of digital transformation. The results of the study indicate a significant differentiation in the risk structure between traditional and digitalized enterprises. It was found that the coefficient of variation of investment returns in digitalized production is 17,3 % higher, but at the same time, the integral indicator of resilience to systemic economic crises demonstrates an excess of 23,8 % compared to traditional enterprises. Cognitive technologies for risk assessment made it possible to identify nonlinear relationships between the level of digital maturity of enterprises and the volatility of investment returns with a determination coefficient of R²=0.78. A multi-level model for assessing investment risks was developed that takes into account the specifics of the digital transformation of industrial systems, which demonstrated a predictive accuracy of 84,2 % on the control sample. The results of the study are of theoretical significance for the development of investment analysis methodology in the context of the digital economy and of practical value for investors, enterprise managers and regulators of the industrial sector.
Keywords: investment risks; digitalization of industry; cognitive technologies; digital transformation; industrial enterprises; multifactor risk analysis; investment attractiveness.

 

M. R. Safiullin (Kazan (Volga Region) Federal University; Center for Advanced Economic Research of the

Academy of Sciences of the Republic of Tatarstan, Kazan); L. A. Elshin (Kazan (Volga Region) Federal University; Center for Advanced Economic Research of the Academy of Sciences of the Republic of Tatarstan; TISBI University of Management, Kazan); Ya. A. Kuznetsov (Center for Advanced Economic Research of the Academy of Sciences of the Republic of Tatarstan, Kazan)

The role and prospects of digital fintech instruments in attracting Islamic capital to the regions of Russia

The aim of the study is to substantiate the prospects for using blockchain in the practice of attracting Islamic finance to the constituent entities of the Russian Federation, as well as to develop and test a methodological toolkit for empirical assessment of macroeconomic externalities generated in this case. The result of the study is assessments that reveal the potential capacity of the market for attracted Islamic finance in the constituent entities of the Russian Federation for the period up to 2030, including within the framework of using blockchain technologies and integrating regional economic systems into the industry of digital Islamic finance.
Keywords: Islamic finance; fintech; blockchain; regional economic systems; sanctions restrictions; investment activity; capital movement; digital financial instruments; macroeconomic development; risk localization.

A. I. Galkin (Financial University under the Government of the Russian Federation, Moscow)

Industrial policy and socioeconomic development: impact on living standards and social stability

This article examines the impact of industrial policy on the socioeconomic development of the country, the standard of living of the population, and social stability. Particular attention is paid to the analysis of the relationship between industrial policy instruments, structural changes in the economy, and quality of life indicators. Based on a systematic review of the literature and econometric modeling of panel data for 28 countries for the period 2000–2020, significant effects of targeted government support for high-tech industries and innovations on economic growth, employment, income, and educational level of the population are revealed. It is shown that active industrial policy aimed at modernizing production, increasing labor productivity, and developing human capital helps to reduce social inequality and increase life satisfaction. At the same time, a nonlinear relationship is established between the scale of government intervention and the dynamics of social indicators, which emphasizes the importance of a balanced approach. The results obtained contribute to the theoretical understanding of the mechanisms of industrial policy and its social consequences, and are also of practical importance for the development of sustainable development strategies. 
Keywords: industrial policy; socio-economic development; standard of living; social stability; structural changes; innovation.

 

O. B. Skripnik (Financial University under the Government of the Russian Federation, Moscow)

Principles and scientific approaches to building a system of criteria for assessing and formulating policy goals in the field of sustainable development and economic security

The theoretically substantiate the principles and scientific approaches to building a system of criteria for assessing and formulating policy goals in the field of sustainable development and economic security of the Russian Federation are shown. A comprehensive analysis of economic and political aspects was carried out using an interdisciplinary approach. The political goals defined in the Strategy of Economic Security of the Russian Federation for the period up to 2030 are clarified and supplemented. Taking into account modern integration processes and the global agenda of sustainable development, in particular within the framework of the BRICS, the political goals of Russia are additionally formulated. Key factors are identified for each of the policy goals, as well as specific criteria to assess the degree to which they have been achieved. The principles and approaches outlined in the article form a methodological basis for building a flexible and scientifically sound system for assessing policy goals that can function effectively in the context of global transformations and high uncertainty.
Keywords: political goals; assessment criteria; sustainable development; economic security; sustainable development goals; ensuring Russia's economic security.

 

S. G. Eremin (Financial University under the Government of the Russian Federation, Moscow)

Problems and priorities of improving land management in Russia

The importance of land plots is accompanied by the fact that land resources are used in the economic activities of the state, and also contribute to improving the quality of life of the country's population. Based on this, state authorities in the field of land management, which have general competence, industry bodies, and various departments have been formed. It has been determined that, at present, a single land management body in Russia is absent, and therefore a unified land management strategy has not been developed and land and agrarian reforms have not been completed. This is a major drawback in the field of land management, which entails imperfections in land and agrarian policy, leads to a shortfall in tax payments to the country's budget, as well as the lack of guarantees for property and contributes to the formation of corrupt and shadow schemes for the turnover of land plots, including industrial ones.
Keywords: land resources, industrial lands, management, policy.

 

V. V. Mironenko, D. A. Rifel (INRTU, Baikal AI Center, Irkutsk)

Review of object tracking technology for analyzing the availability of personal protective equipment and compliance with safety regulations in real time

A review of a number of publications is conducted, as a result of which various methods, algorithms and technologies were identified that can be used to monitor compliance with safety regulations and wearing personal protective equipment. The implementation of object tracking technology, using technologies based on the use of machine vision cameras and specialized software, helps to improve labor safety, reduce the influence of the human factor, timely tracking, detection and prevention of violations of labor safety.
Keywords: computer vision; machine vision; cameras; neural networks, object tracking.

 

I. V. Deryabin (Togliatti State University, Togliatti)

On the issue of reducing transport noise

The aim of the study is to determine the influence of the type of road intersection on the level of road noise. An experimental method was used to measure the noise characteristics of the traffic flow (equivalent sound level) at road intersections of various types. The paper presents the results of an experimental assessment of noise levels at intersections with cross and traffic circles in different day periods with different traffic flow intensities. It is concluded that it is appropriate to use traffic circles to reduce the intensity of the acoustic environmental impact from the roadway.
Keywords: traffic noise; intersection; freeway; traffic circle; cross circle.

 

P. S. Turzin (Scientific Research Institute of Healthcare Organization and Medical Management Department of Health of the City of Moscow, Moscow); K. E. Lukichev (Financial University under the Government of the Russian Federation, Moscow)

On the role of regional authorities in supporting the health of industrial workers

In modern conditions of industrial activity of employees of large industrial enterprises, characterized by increased exposure to adverse factors, the need for an integrated approach to maintaining and strengthening their physical health is being actualized. Of particular importance is the assessment of the effectiveness of the regional workers' health management system at the level of the constituent entities of the Russian Federation. The methodology of the conducted research includes a survey of the heads of regional government bodies using a specialized survey methodology containing 40 structured questions with the possibility of both multiple choice and free response. The questionnaire was sent to all 89 subjects of the Russian Federation, while the data set obtained from 59 regions was processed and systematized. The analysis of the survey results made it possible to identify the current state of the studied issues in a significant part of the subjects of the Russian Federation and identify key factors that have both a limiting and stimulating effect on the development of the physical health management system for industrial personnel, as well as the place and role of regional authorities in maintaining the health and longevity of industrial workers.
Keywords: occupational health; occupational diseases; occupational safety; preventive care; regional healthcare system; industrial medicine.

 

N. K. Popadyuk, O. A. Sagina, S. G. Eremin (Financial University under the Government of the Russian Federation, Moscow)

Comparative analysis of digitalization of cities

The study demonstrates the differentiation of digital transformation processes in municipalities of the Russian Federation, characterized by different degrees of digital maturity. The comparative analysis covers three representative cities representing different positions in the spectrum of technological development, and the city of Moscow as an exemplary model of intellectualization of the «Smart City» model, although it is not a municipality. The conducted multivariate analysis made it possible to identify the key determinants of successful digital transformation of the urban environment and formulate scientifically based recommendations for optimizing digitalization processes in municipalities at various stages of technological development. The object of the study is the city as a socio-economic managed system. The subject is the digitalization of urban management as the basis for the «Smart City» technology. The research method is comparative studies of digitalization models of urban management implemented in Russia.
Keywords: digitalization of cities; smart city; digital transformation; municipal management; urban infrastructure; information technology; digital services; IQ index of cities; lean technologies; artificial intelligence; electronic platforms; transport innovations; digital ecosystem.

 

R. T. Dulambaeva (Academy of Public Administration under the President of the Republic of Kazakhstan, Astana, Republic of Kazakhstan); Sh. U. Niyazbekova (Financial University under the Government of the Russian Federation; Moscow Witte University, Moscow); M. S. Pestova (Russian State University of Social technologies, Moscow); E. G. Kosheleva (Donetsk State University, Donetsk); R. K. Sabirova (Kh. Dosmukhamedov Atyrau University, Atyrau, Republic of Kazakhstan); M. G. Goigova (Ingush State University, Magas)

Development and application of technologies in the forging and stamping business and its significant impact on the economy

The article examines forging and stamping production, which is related to the mechanical engineering industry and is engaged in the production of metal products by molding them using mechanical and thermal processes. An analysis of forging and stamping and its impact on the economy is conducted. The article presents leading and developing companies in the field of forging and stamping of metals and related industries, statistical data on forging and stamping of metal in the USA, forecast data for a number of years, etc.
Keywords: technological processes; waste processing technologies; effective solutions; saving time and effort; impact on the economy; industries.

 

O. A. Zhigunova, M. S. Gusarova (Industrial University of Tyumen, Tyumen)

Time management for the development of oil and gas engineering

The article considers the issues of time management application for sustainable development of oil and gas engineering in the conditions of functioning in the market with limited human resources. The article provides a description of the situation in the oil and gas engineering industry, outlines the problems and prospects for its development. The role of human resources in ensuring sustainable development is substantiated and time management tools are proposed to ensure increased efficiency of human resources use. A comprehensive system for implementing time management at oil and gas engineering enterprises is proposed.
Keywords: time management; oil and gas engineering; human resources management; sustainable development.

 

M. V. Polevаya (Financial University under the Government of the Russian Federation, Moscow)

The impact of digital modeling on the development of human capital and organizational culture of industrial enterprises in the context of digital transformation

The article is devoted to the study of the influence of digital modeling on the development of human capital and organizational culture of industrial enterprises in the context of digital transformation. The relevance of the topic is due to the rapid introduction of digital technologies in production processes and the need to adapt to new realities. The key effects of digital modeling are identified and its role as a driver of human capital development and transformation of organizational culture is substantiated. The empirical base is formed by the data of a survey of 120 enterprises of various industries. It is revealed that digital modeling contributes to the development of personnel competencies, stimulates innovative activity, and increases employee engagement. It is shown that the effects vary depending on the level of digital maturity of enterprises. The need for proactive adaptation of organizational culture to the challenges of digitalization is substantiated. The results of the study are significant for the development of human capital theory and can be used in developing strategies for the digital transformation of enterprises.
Keywords: digital modeling; human capital; organizational culture; digital transformation; industrial enterprises; competencies; innovations.

 

O. T. Ergunova, A. G. Somov, A. A. Sedyakina (Peter the Great St. Petersburg Polytechnic University, St. Petersburg)

The impact of digital technologies on the labor market in the context of the heterogeneity of megacities

The purpose of this article is to analyze the impact of digital technologies on social and labor relations in megacities, taking into account differences in the level of digitalization, industry specialization and economic potential, taking into account the transformation of the mechanism of interaction between employees and employers in the context of new industrialization. Results of the study showed that megacities with a high degree of digitalization, such as Moscow and St. Petersburg, have higher indicators of human capital and a higher level of implementation of digital solutions. While Yekaterinburg and Novosibirsk, with a lower level of digitalization, face limited investments and industry specifics, which hinder development. The total digital capital in Moscow and St. Petersburg is significantly higher than in Novosibirsk, and there is a gap between the basic and advanced digital skills of employees, which indicates the need for further development of digital competencies. The study confirms that megacities with a high level of digitalization demonstrate better adaptation of workers to new technologies, which confirms the importance of digital skills for human capital. However, there is a gap between basic and advanced digital competencies, which requires additional training and professional development efforts. To reduce digital inequality in megacities, investments in digital infrastructure and the development of educational programs aimed at adapting the labor market to the digital economy are needed.
Keywords: social and labor relations; megacities; digitalization; blockchain; smart contracts; neural network technologies; labor market; skills portrait; digital economy.

 

E. R. Zhdanov, A. V. Volkov, A. V. Kryukov, D. S. Stepynin, O. S. Kharina (MIREA - Russian Technological University, Moscow)

Features of designing radio-transparent high-temperature composite material

The article discusses the main aspects of the design and manufacture of materials, the phthalonitrile group was used as connecting components, as well as the possibility of molding parts from them, taking into account the required technical characteristics. The interaction of the obtained radio-transparent prepregs with electromagnetic radiation in the microwave range was studied in order to analyze the integrity of the signal. The main approaches to the development of radiotransparent materials using domestic components are proposed. A new approach to the selection of components when creating RPMs is a comprehensive assessment of their characteristics, allowing the selection of rational source materials and the creation of an optimal algorithm for the technological process of manufacturing a structure (part). The obtained results allow achieving high efficiency and stability in terms of dielectric parameters of RPM, minimizing manufacturing costs by optimizing a number of pseudo-optimal design solutions. The obtained results can be used in designing a wide range of composite structures that have radio transparency requirements.
Keywords: microwave electromagnetic radiation; radio transparency; dielectric loss tangent; dielectric losses; prepreg; VRKM.