Articles

• 1

  Regulation of Artificial Intelligence in Education

  Authors: A.V. Zazhigalkin, FSAEI FVT Academy for Standardization, Metrology and Certification (Training) (FSAEI FVT ASMS), Dr. (Ec.) 

  T.T. Mansurov, Commonwealth of Independent States Executive Committee, FSAEI FVT ASMS, PhD (Law) 

  O.V. Meretskov, FSAEI FVT ASMS, Corresponding Member of Academy of Informatization of Education, PhD (Ped.), meretskov.ov@asms.ru
  The article is an overview of modern research in the field of the application of artificial intelligence technologies in education, as well as domestic and foreign experience in the field of legislative regulation of this area (GOST R system of standards, the system of voluntary certification Intellometrica, EU Directive N 8115/21 Artificial Intelligence Act). It is noted that in the EU, for the first time in world practice, the mechanism for regulating artificial intelligence systems was described in relation to the most important areas of activity from the point of view of risks, which include education. It is concluded that it is necessary to create a mandatory certification system for software and equipment using artificial intelligence technology for use in education.

  DOI: 10.24412/1993-8780-2024-6-03-10

  
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• 2

  Component Base Composition Quality Сontrol and Conventional Graphic Symbols

  Authors: Yu.A. Antokhina, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), Prof. Dr. (Ec.), antoxina@guap.ru 

  E.A. Frolova, FSAEI HE SUAI, Assoc. Prof. Dr. (Tech.), frolovaelena@mail.ru 

  K.V. Epifantsev, FSAEI HE SUAI, Assoc. Prof. PhD (Tech.), epifancew@gmail.com 

  A.S. Tur, FSAEI HE SUAI, Liona1996@yandex.ru
  The use of machine-readable standards in the Russian design documentation system for the rapid integration of complex 3D models and databases into technical processes and product quality control units is considered. Also, as well as the scientific problem of the of сonventional graphic symbols presence in foreign manufacturers models. Obscure foreign elements introduced by ISO standards into the GOST R system make it difficult to qualitatively adapt drawings obtained using a machine-readable interface to the realities of Russian production. It determines the need for high-quality translate of drawings. In general, the deployment of machine-readable standards in Russia has steady trends towards increasing the potential of electronic documents.

  DOI: 10.24412/1993-8780-2024-6-11-19

  
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• 3

  On the Аpproach to the Technology Classification

  Authors: D.O. Skobelev, Research Institute Environmental Industrial Policy Center (EIPC), Dr. (Ec.) 

  T.V. Guseva, EIPC, Prof. Dr. (Tech.)
  The article discusses problems associated with the development of a technology classifier worked out to implement the Strategy of Scientific and Technological Development of the Russian Federation. We have shown that the classifier based on the principle of a list of currently known solutions can become an obstacle to inventing and implementing new technologies necessary for the development of the country. The article emphasizes that the technology classifier can be built in concert, and not in contradiction with existing classifiers. It should be based on a standardized description format, in which the essential features of the classified objects should be highlighted. Authors propose considering the purpose, core, and periphery of the technology as such signs. To facilitate subsequent computer processing, each of the features can be ordered in the space of existing classifiers.

  DOI: 10.24412/1993-8780-2024-6-20-27

  
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• 4

  Model for Assessing the Trend Quality Using Fuzzy Logic Method

  Authors: Yu.A. Antokhina, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), Prof. Dr. (Ec.), antoxina@guap.ru 

  S.A. Nazarevich, FSAEI HE SUAI, Assoc. Prof. PhD (Tech.), albus87@inbox.ru 

  D.S. Shchukina, FSAEI HE SUAI, shchukinadaria00@gmail.com
  The paper proposes a model for assessing the maturity level of the value innovation trend based on the theory of fuzzy sets, which allows us to reliably assign the emerging trend to one of the levels, give a visual assessment of the prospects of the results of innovative activities. It is noted that the model has practical applicability due to the ability to classify a trend at any maturity level with a high degree of accuracy and reliability. In addition, using the model it is possible to identify problem areas and determine the necessary strategies of the company to adapt to market changes to improve the efficiency and competitiveness of innovations.

  DOI: 10.24412/1993-8780-2024-6-28-32

  
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• 5

  Modeling of Technological Parameters in Additive Manufacturing

  Authors: A.V. Smirnov, Bauman Moscow State Technical University, smiandrei@bmstu.ru
  In recent years, machine-building enterprises have been actively adopting the approach of customized production organization, where production parameters can be varied to suit any order. This is connected with the rapid development of additive technologies implemented in production, which allow for the manufacturing of metal parts with complex shapes and the control of the metal microstructure by adjusting the process parameters. This makes it possible to produce products with unique mechanical properties and complex internal microstructure. The application of advanced additive manufacturing technologies involves establishing a set of parameters for each sub- process that will influence the quality of the final product. In the article I have analyzed the primary parameters that influence the quality of the final product in additive manufacturing. It discusses a binary multicriteria mathematical model for selecting an optimal parameter vector based on the chosen additive technologies.

  DOI: 10.24412/1993-8780-2024-6-33-36

  
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• 6

  Project Risk Management Methods

  Authors: E.A. Frolova, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), Assoc. Prof. Dr. (Tech.), frolovaelena@mail.ru 

  S.А. Atroshenko, FSBIS Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences, Prof. Dr. (Phys.-Math.), satroshe@mail.ru 

  A.А. Kaplieva, FSAEI HE SUAI, alex.arg27@yandex.ru
  Risk management is an activity within the framework of project management, which is becoming increasingly important due to the modern and dynamic production. Before starting a risk reduction program, it is necessary to identify the sources of risks and their potential consequences. In the article the methods of project risk assessment and management, hierarchical analysis method and grey clustering method are reviewed. The use of new methods for more accurate risk assessment is suggested, as well as bringing the assessment closer to reality. Future development of integrated and versatile tools may lead to widespread use of risk management principles, which will enhance competitive advantage in business. 

  DOI: 10.24412/1993-8780-2024-6-37-41

  
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• 7

  A Model for Labor Resources Distribution in a Hybrid Production Line

  Authors: A.V. Vinnichenko, FSAEI HE St. Petersburg State University of Aerospace Instrumentation, alex23rain@gmail.com
  The problem of hybrid flow production is very difficult in most cases, and planning such production is a complex combinatorial task. The paper presents a model of production planning, which is characterized by the possibility of work execution by more than one work group with the possibility of parallel execution of work. The developed model of production planning allows to optimize the distribution of labor resources in hybrid flow production, taking into account various constraints and efficiency criteria. It can be applied at enterprises of various industries in the procedure of making informed decisions to optimize production processes and improve the efficiency of the enterprise as a whole.

  DOI: 10.24412/1993-8780-2024-6-42-45

  
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• 8

  Quality of Technological Processes in Additive Instrumentation: Machine Learning Models

  Authors: A.G. Chunovkina, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), Senior Researcher Dr. (Tech.), a.g.chunovkina@vniim.ru 

  A.P. Yastrebov, FSAEI HE SUAI, Prof. Dr. (Tech.), ap.guap@gmail.com 

  A.V. Chabanenko, FSAEI HE SUAI, PhD (Tech.), a@chabanenko.ru 

  M.D. Rassykhaeva, FSAEI HE SUAI, mitschiru@ya.ru
  Traditional quality control methods often turn out to be inadequate for the unique conditions and requirements imposed on production processes in additive instrumentation. In this situation, machine learning appears to be a powerful tool that can transform the industry. The main technological challenges of additive production are the collection and processing of large amounts of data, as well as the development of algorithms capable of operating under conditions of high uncertainty. Machine learning methods enable continuous data collection in real time. With their help, you can constantly analyze the process and immediately adjust its parameters. In particular, predictive analysis algorithms can evaluate potential defects based on current printing conditions and historical data, allowing operators to make adjustments to the process before errors occur.

  DOI: 10.24412/1993-8780-2024-6-46-50

  
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• 9

  On the Issue of Risk Аnalysis in Аssessing a Complex Quality Indicator

  Authors: V.A. Tushavin, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), Dr. (Tech.), tushavin@gmail.com 

  Ya.V. Tushavin, FSAEI HE SUAI, yan@tushavin.ru 

  A.S. Tur, FSAEI HE SUAI, Liona1996@yandex.ru
  The article discusses the algorithm for generating a matrix of random weights, robust scaling techniques, and a methodological approach to risk assessment of a complex quality indicator using sensitivity analysis. These complex studies and analyses conducted by the authors using simulation modeling and modern statistical tools contain certain innovations and allow them to further solve even such problems as assessing the possibility of using inauthentic products in import substitution and in general a wide range of tasks related to comparisons and evaluations of multiparametric objects in economics and management. The results of the work can be useful to researchers dealing with problems related to solving qualimetric tasks, as well as the task of implementing the methodology of Six Sigma process design.

  DOI: 10.24412/1993-8780-2024-6-51-55

  
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• 10

  System for Improving the Quality of Mobile Robot Actuators Control

  Authors: A.V. Rysin, FSAEI HE St. Petersburg State University of Aerospace Instrumentation (FSAEI HE SUAI), a.rysin@guap.ru 

  A.O. Smirnov, FSAEI HE SUAI, Assoc. Prof. Dr. (Phys.-Math.), alsmir@guap.ru 

  M.D. Yaushkina, FSAEI HE SUAI, qwakenqwaken@yandex.ru
  
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Content / Abstracts