AHMED SOLIMAN MOHAMED SHERIF EL SAYED (NSTU; Lavrentyev Institute of Hydrodynamics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk)

Numerical study of process operations in the production of aircraft parts (monograph)

The main goal of modeling in the production of aircraft is to ensure high accuracy of assembly of aircraft products, flexibility and reduce the time of their manufacture. In addition, to reduce errors in assembly and manufacture of tooling (devices) for specific aircraft products. As a rule, the process of manufacturing aircraft products is complex and is carried out in the process of assembly and disassembly. As for the complexity of the assembly process of an aircraft product, these studies illustrate a systematic analysis of the technologies for modeling and visualization of the process of manufacturing aircraft parts. The presented studies: cutting titanium alloy VT6, profiling on a four-roll sheet bending machine, friction stir welding of 45 sheet steel, high-speed angular impact welding are the key technologies and solution for the implementation of the visualization system of the aircraft production process. Then the manufacturing modeling environment is implemented, based on the virtual reality modeling language of the LS-DYNA software. In these studies, the technology for modeling the aircraft production process was divided into modeling and visualization systems. The simulation process includes production factors, process equipment, tools and fixtures. LS-DYNA software includes the relevant simulation results and adds the necessary text technologies to simplify the understanding of the concept using simulation methods for processing the results. The study has practical value for the modern aircraft industry, since it allows us to propose a process for simulating an aircraft product based on computer 3D modeling. LS-DYNA is a useful program with a limited number of components, suitable for reproducing complex problems. It is used in mechanical engineering, aviation and space industry and can be used to simulate tests such as collisions and aircraft crashes.
Keywords: orthogonal cutting; Galerkin method; sawtooth chip; profiling; longitudinal deformation; limiting strain diagram / FLD; friction stir welding; SPH interpolation; rotating tool; angular impact welding; metal jet; meshless Lagrange method; smoothed particle hydrodynamics.

 

M. A. Petrov, Tran Dinh Hung (Moscow Polytechnic University, Moscow)

Study of the technological parameters’ impact on defect formation during a microdrawing process by means of FE simulation

The paper evaluates the mutual impact of process parameters during micro-drawing of a copper billet for three scale factors. Based on the results of numerical simulation using Abaqus software, a map with the favorable technological parameters window for the microdrawing process has been obtained to avoid the most frequent defects, such as folds on the wall and critical thinning at the transition zone between the cup’s wall and the bottom. A linear regression equation showing the relationship between the maximum deformation force, friction coefficient and deep drawing coefficient is derived.
Keywords: micro-drawing; size effect; friction coefficient; drawing coefficient; folding; thinning; blankholder force; FEM; Abaqus.

 

A. V. Lutyanov, D. K. Obukhov (MIREA – Russian Technological University, Moscow)

Various solutions in the field of simulation modeling in the engineering industry

Various solutions in the field of simulation modeling in the mechanical engineering industry are studied. The efficiency of using such modeling in specialized application environments for designing and optimizing production systems for manufacturing metal-intensive parts at mechanical engineering enterprises is proven. Key requirements for programs for simulation modeling and criteria for their selection are determined. An analysis of the capabilities of software environments of domestic and foreign developers represented on the Russian market is conducted.
Keywords: simulation modeling; mechanical engineering technology; automation of mechanical engineering; software solutions for simulation modeling.

 

R. A. Nezhmetdinov, R. A. Nezhmetdinova (MSTU «STANKIN», Moscow); D. T. Bautdinov, D. V. Nikitin (State University of Management, Moscow)

Application of additive technologies in transport and agricultural engineering

The rapid development of additive manufacturing or 3D printing over the past decades has had a significant impact on many industries, including transport and agricultural machinery. These technologies offer new approaches to manufacturing complex geometric objects, reducing material costs and decreasing the weight of products. The article explores the potential for using additive technologies in these industries, as well as analyzes their advantages and challenges. The study takes an analytical approach that includes a comprehensive review of existing 3D printing technologies used in transport and agricultural machinery. The focus is on the analysis of methods such as selective laser sintering and laser selective melting, as well as the use of various materials, such as metals and composites. Key areas of application of additive technologies in transport and agricultural machinery are identified. The main advantages include reducing the cost of producing individual parts, increasing the efficiency of designing complex assemblies and reducing the weight of components without losing strength characteristics. Examples include the production of lightweight parts for cars, engine components and agricultural machinery assemblies, which can improve the overall productivity of machinery. Despite the above advantages, the widespread implementation of additive technologies in these industries faces a number of problems, such as high equipment costs, limitations in the materials used, and standardization issues. In addition, further development of the regulatory framework is required to ensure the safe and efficient use of AM in industry.
Keywords: additive technologies; transport; transport engineering; agricultural engineering; materials.

 

N. A. Lebedev (Federal State Budgetary Educational Institution Institute of Economics of the Russian Academy of Sciences, Moscow); S. V. Zubkova (Financial University under the Government of the Russian Federation, Moscow)

Modernization of interaction between the industrial and financial sectors as a priority component of Russia’s technological and digital sovereignties

A set of issues related to the problem of structural modernization of the interaction between the industrial and financial sectors of the economy as a primary component of technological sovereignty and digital sovereignty of Russia is briefly analyzed. An important component of structural modernization in industry is the deepening of interaction between the industrial and financial sectors of the economy with participation in ecosystems. It is shown that in relation to the vector of technological and digital sovereignty, an integrated approach laid the direction of structural modernization, which could be carried out, most of all, in promising areas of growth in a number of leading industries, in particular, in the automotive industry, the fuel and energy complex, retail trade (with its technological vector – marketplaces and digital platforms), in the manufacture of pharmacological products, etc. It is concluded that the structural modernization of the interaction between the industrial and financial sectors of the economy as a primary component of technological sovereignty requires the restoration of the production process, which simultaneously determines the need to introduce innovative domestic technologies based on the development of digital platforms with the participation of the banking sector and becomes an urgent necessity. When writing the work, general and special research methods were used.
Keywords: technological sovereignty; digital sovereignty; industries; innovative development; new technologies; artificial intelligence; investment in innovation; technology sector; import substitution; banking sector; embedded financial services; digital platforms.

 

E. L. Kruglova, S. A. Yushkova (Financial University under the Government of the Russian Federation, Moscow)

Development and analysis of the efficiency of algorithms for approximating solutions of nonlinear partial differential equations using deep learning methods

The application of deep learning methods for solving nonlinear partial differential equations (PDEs) is a promising direction at the intersection of computational mathematics and artificial intelligence. Despite significant progress in this area, the issues of the optimal choice of neural network architecture, effective consideration of boundary conditions and theoretical justification of the convergence of neural network methods for various classes of nonlinear PDEs remain unresolved. The objective of the study is to develop and mathematically justify new methods for approximating solutions to nonlinear PDEs using deep neural networks, as well as their theoretical analysis and numerical comparison with classical numerical methods. The criteria for selecting the optimal neural network architecture depending on the properties of PDEs are established. An effective method for taking into account boundary conditions is developed, ensuring the stability of the solution. Adaptive optimization schemes are proposed that take into account the specifics of nonlinear PDEs. Theoretical estimates of the approximation error and convergence rate are obtained for various classes of nonlinear PDEs. The developed methods demonstrate high efficiency in solving a wide class of nonlinear PDEs, surpassing classical numerical methods in accuracy and computational efficiency for multidimensional problems. The theoretical results open up new prospects for substantiating and analyzing neural network methods for solving PDEs. Further research will be aimed at developing hybrid methods and expanding the scope of application to systems of coupled nonlinear PDEs.
Keywords: nonlinear partial differential equations; deep learning; approximation theory; numerical methods; neural networks.

 

G. A. Gareeva (Kazan National Research Technical University named after A. N. Tupolev - KAI, Naberezhnye Chelny); A. A. Mirsaitova, Z. Sh. Aglyamova (Kazan Innovative University named after V. G. Timiryasov, Naberezhnye Chelny); A. G. Fayzullina, V. M. Nigmetzyanova (Kazan (Volga Region) Federal University, Naberezhnye Chelny Institute, Naberezhnye Chelny)

Automation of the process of accounting and monitoring of computer and network equipment

The process of developing modules of the automated system of accounting and monitoring of computer equipment in the corporate network is presented. The modules allow for more efficient network management, and their development is an important step in ensuring the security and efficiency of the corporate network. These modules allow you to monitor the status of network devices, identify problems and eliminate them. They help improve the management of network resources and increase its performance.
Keywords: automation; information systems; accounting; monitoring; computer and network equipment; corporate network.

 

O. E. Ustinova, T. A. Ason, T. B. Izzuka, S. N. Milovidova (Financial University under the Government of the Russian Federation, Moscow)

Digitalization of medium-high technologies in industries

The manufacturing landscape has undergone significant changes caused by the rapid development of digital technologies. Recently, the application of digital tools in industry has opened up unprecedented opportunities for resource acquisition, collaboration, development of innovative products and services, and entry into new markets. Despite the growing recognition of digitalization as a vital component of industrial production, issues related to the benefits and effectiveness of digital technologies, their search, implementation, and adaptation in the activities of industrial companies require careful analysis. Understanding the current state of the digitalization level will help industrial companies achieve successful transformations that are critical in the competitive business environment. The article discusses the factors contributing to the development of digitalization of industrial companies, based on which the digitalization index of medium-high-level industries is calculated. The obtained results can serve as one of the directions of research regarding the possibilities of digital transformation and development of digitalization.
Keywords: digitalization index; mid-tech industries; digital technologies; industrial enterprises.

 

O. V. Brizhak (Financial University under the Government of the Russian Federation, Moscow); Sh. U. Niyazbekova (Atyrau University named after Kh. Dosmukhamedov, Atyrau, Republic of Kazakhstan)

Socio-economic aspects of industrial development in the age of digital technologies

The increasing turbulence of processes in the modern world causes the generation of high risks and increases the level of uncertainty, which leads to a significant decrease in the accuracy of forecasts and a corresponding reduction in the possibilities of strategic planning in all areas of development. The regular influence of technological transformations actualizes the value of accurate and up-to-date knowledge of the nature, content and specific forms of qualitatively new phenomena of the modern evolutionary process, which include digital technologies. Such knowledge forms the necessary cognitive platform for ensuring global competitiveness and sustainable development of the Russian economy, its spheres, industries and individual enterprises. The article examines the socio-economic aspects of industrial development based on digital technologies, corresponding to the new paradigm of development of the Russian economy with the regular impact of external restrictions on access to the most important resources of world markets. The conclusion is substantiated about the need to implement a special algorithm for the strategy of socio-economic development of Russian industry in the era of the dominance of digital technologies. The study was carried out on the basis of a systematic approach, which is due to the systemic nature of the analyzed process of development of the industrial sector, as well as the similar nature of the conditions for this process.
Keywords: Russian industry; competitiveness; digital technologies; artificial intelligence; public policy; regional projects; import substitution.

 

R. O. Kiselyov (V. I. Vernadsky Crimean Federal University, South-Eastern Academy (branch), Simferopol)

Assessment of innovative activity and potential of economic entities of the regions of the Russian Federation in the conditions of digital transformation

In the context of digital transformation, it is of particular importance to assess the innovative activity and potential of economic entities in the regions of the Russian Federation by considering a conceptual model of interaction between elements of the innovation system in the context of digital transformation. It is assessed the innovative activity and potential of economic entities in the regions of the Russian Federation in the context of digital transformation.
Keywords: innovative activity; innovative potential; economic entities of Russian regions; digital transformation.

 

M. R. Safiullin (Kazan (Volga Region) Federal University, Center for Advanced Economic Research of the Academy of Sciences of the Republic of Tatarstan, Kazan); M. D. Sharifullin (Center for Advanced Economic Research of the Academy of Sciences of the Republic of Tatarstan, Kazan); L. A. Yelshin (Kazan (Volga Region) Federal University; Educational Institution «University of Management «TISBI», Kazan)

Assessing macroeconomic externalities generated by the integration of national financial systems into DeFi using the Russian Federation as an example

Following the basic conclusions of scientists and international development institutions (World Economic Forum, Organization for Economic Cooperation and Development, Bank for International Settlements, etc.), the DeFi sphere has significant potential for optimizing the Fintech sector, including its supranational level. However, how this can affect the development of individual countries and regions integrated into the new digital ecosystem is still a fairly open question. Based on this conclusion, this study developes a macroeconomic model that assesses the possible effects for the national economy of the Russian Federation within the framework of the integration of its financial system into global innovative technological solutions, which undoubtedly include DeFi.
Keywords: blockchain; decentralized finance; foreign economic activity; international payments; sanctions pressure; macroeconomic externalities; gross domestic product.

 

A. B. Mottaeva (Financial University under the Government of the Russian Federation, Moscow)

Innovative and strategic transformations of the Russian regional economy in the digital age

This article examines the innovative and strategic transformations of the economy of Russian regions in the digital age. In recent years, the speed of development of the mobile Internet, large amounts of data and artificial intelligence have made it possible to create and explore the possibilities of digital transformation at all levels of government, including regional management. Of course, transformations and iterations of digital technologies lead to constant changes in socio-economic, territorial, distributive, and legal forms of government. Today, the transformation of regional development is moving in two directions – digitalization of the economy and digital industrialization. In the future, all innovative transformations of the regions will require systematic reforms that support and adapt the digital economy, create a social environment and increase the level of the risk response system. Cultivating new kinetic energy for the economic and social development of the Regions is an inevitable choice that contributes to the implementation of a new historical leap forward. The digital economy is based on factors of production, modern information networks, integration and application of information and communication technologies, as well as the digital transformation of all factors, as an important driving force for the promotion of a more unified new form of efficiency. In this context, the current mechanisms of innovative and strategic transformations of the regional economy in the digital age are studied in detail. The analysis of the impact of the new round of the technological revolution, new paradigms of regional policy and economics, mechanisms of transition to new levels, such as the digital economy, digital transformations of strategies of Russian regions, determined the relevance of the chosen research topic. In the future, the conducted research will allow for a deeper study of priority areas, trends and laws of regional development and continue to contribute to the qualitative development of digital transformations by optimizing strategies, systems and management mechanisms.
Keywords: digital economy; digital age; digital technologies; digitalization; digital transformation; digital maturity; regional digital transformation strategies; strategic priorities; regions of Russia; innovative development.

 

L. I. Alibalaeva, V. M. Savinova (Plekhanov Russian University of Economics, Moscow)

Customer profiling model based on clustering and associative rule as a way to enhance the effectiveness of organization's marketing strategy

The article is devoted to the customer profiling by developing a model ensemble based on associative rules and clustering. The approaches to the marketing strategy development in general and its features in organizations are analyzed, taking into account the needs and preferences of clients. The use of digital technologies and intelligent models is proposed to improve the marketing strategy effectiveness based on customer orientation and the past experience of the organization. The results of the analysis and the model ensemble development make it possible to identify the most popular services, form a more effective marketing strategy focused on clusters, and increase the conversion of advertising campaigns.
Keywords: customer profiling; associative rules; clustering; machine learning; marketing strategy; management; modeling.

 

O. V. Brizhak, V. Eknigk (Financial University under the Government of the Russian Federation, Moscow); Sh. U. Niyazbekova (Moscow Witte University, Financial University under the Government of the Russian Federation, Moscow); M. D. Saiymova (Zhubanov University, Aktobe, Republic of Kazakhstan)

Strategy for attracting and retaining banking clients in a highly competitive environment: new technologies BNPL service

The study examines various technologies and marketing strategies used by Russia's leading banks to attract and retain customers in the financial services market. BNPL programs managed by third-party loan specialists are becoming more popular and affordable. In fact, according to one survey, up to 25 % of Americans used BNPL as an option. And although BNPL providers charge retailers for using the service, they compensate by increasing sales. The authors analyzed the technologies used, marketing tools of banks and opportunities for their further development and increasing the customer base. Recommendations for banks on improving marketing strategies are considered.
Keywords: bank; competition; bank client; banking sector; technology; customer engagement.

 

A. V. Shmeleva (State University of Education, Moscow)

Economic significance of profit in the implementation of training programs in production and their impact on the optimization of production processes and product quality

This article is dedicated to the study of the economic effect of implementing training programs in production in the context of optimizing production processes and improving product quality in the industrial sector. Based on a critical analysis of current literature and empirical data, key factors and mechanisms of the influence of corporate training on labor productivity, operational efficiency, and enterprise competitiveness are identified. The author proposes terminology and a methodology for assessing the economic effectiveness of educational initiatives, taking into account industry specifics. The conducted study fills gaps in the understanding of the strategic role of employee training for the sustainable development of industrial companies. The obtained results are of high theoretical and practical significance, opening up prospects for further development of models and tools for managing human capital in the production sphere. The article makes an original contribution to the development of the subject area at the intersection of economics, management, and pedagogy.
Keywords: corporate training; labor productivity; product quality; human capital; industry; economic efficiency; process optimization.

 

R. D. Golya (RosNOU; ROENTGEN KOMPLEKT Ltd, Moscow)

Import substitution resources in the production of components and assemblies for medical equipment that create an effective radiation dose assessment system

The modern development of digital technologies is increasingly penetrating into the field of medicine at almost all levels.  In this article, we consider the modeling of a deep convolutional neural network trained using MC modeling to estimate the radiation dose. The study proposed a new DCN-based method for calculating 3D radiation dose maps during X-ray procedures, taking into account the morphology of the patient and the composition of his organs, as well as imaging settings. A convolutional neural network is capable of obtaining information from a database created using computer modeling with high accuracy, with minimal errors in relation to the skin, pancreas and the entire abdominal cavity. A short calculation time was achieved, which makes the developed approach a potential solution for use in commercial dose monitoring and reporting systems.
Keywords: import substitution; production of components and assemblies in forging and stamping production; neural networks; computer modeling; radiation load; Monte Carlo method.