DOI: 10.33917/es-3.195.2024.68-79

This work continues to examine the model-oriented system engineering [1–3] and at the same time presents an approach based on streamlining and sequentially complex complementing of MBSE formats according to the principle “from simpler to more complex” with the subsequent study of the possibility to include the considered modeling formats in tool platforms of digital engineering. The main focus is made on the systematic orderliness and logic of the approach presentation, with the understanding that in the subject area there is a wide range of divergent definitions (the well-known effect of the language of the Tower of Babel builders).

References:

1. Kondrat’ev V.V. Model’no-orientirovannyy sistemnyy inzhiniring 2.0 [Model-Based Systems Engineering 2.0]. Moscow, MF TI, 2021.

2. Garichev S.N., Gorbachev R.A., Davydenko E.V., Dzhaparov B.A., Kondrat’ev V.V. Model’no-orientirovannyy inzhiniring fiziko-tekhnicheskikh, informatsionnykh i intellektual’nykh system [Model-Based Engineering of Physical, Technical, Information and Intelligent Systems]. Trudy MFTI, 2022, vol.

14, no 2.

3. Kondrat’ev V.V., Tishchenko E.B. Arkhitekturnyy inzhiniring gibridnykh modeley, vklyuchayushchikh tsifrovye dvoyniki i mashinnoe obuchenie [Architectural Engineering of Hybrid Models Incorporating Digital Twins and Machine Learning]. Ekonomicheskie strategii, 2023, no 5(191), pp. 94–99, DOI:

10.33917/es-5.191.2023.94-99

4. Semin A.N., Tishchenko E.B., Kislitskiy M.M., Kurdyumov A.V. Razvitie metodologicheskikh polozheniy proektnogo upravleniya v sfere obespecheniya tekhnologicheskogo suvereniteta APK [Development of Methodological Provisions of Project Management in the Field of Ensuring Technological Sovereignty of the Agro-Industrial Complex]. Fundamental’nye i prikladnye issledovaniya kooperativnogo sektora ekonomiki, 2022, no 4, pp. 3–10.

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8. Potyupkin A.Yu., Chechkin A.V. Iskusstvennyy intellekt. Na baze informatsionno-sistemnoy izbytochnosti [Artificial Intelligence. Based on Information System Redundancy]. Moscow, Kurs, 2022.

9. Organizatsionnyy dizayn. Resheniya dlya korporatsiy, kompaniy, predpriyatiy: Mul’timediynoe uchebnoe posobie + Praktikum na CD-R [Organizational Design. Solutions for Corporations, Companies, Enterprises: Multimedia Textbook + Workshop on CD-R]. Pod red. V.V. Kondrat’eva. Moscow, INFRA-M, 2018 (Upravlenie proizvodstvom).

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DOI: 10.33917/es-5.191.2023.94-99

In modern engineering of complex technical systems [1] digital twins and artificial intelligence systems started to be applied, while these subsystems have their own methods and tools for systemic, mathematical and computer modeling. Lack of a normalized approach to combining data from disparate sub-systems into a single system results in a “one-off” assembly methodology or in creation of unique digital models and intelligent systems, which impedes their further transformation into more complex both technical and intelligent systems. In this regard, the search for a standard form of representing such subsystems into a single system becomes relevant, along with the task of developing a methodology for the unified design and production of intelligent systems based on the use of model-oriented system engineering [2, 3, 4]. The work names and systematizes methods and techniques for such developments, demonstrates a standard approach to a normalized platform representation of models of various subsystems, which initially have their own methods and presentation tools; results of a normalized policy for constructing a platform of models from various subsystems for an anthropomorphic robot and spacecraft are described. Within the framework of the presented example, complementary methods of digital multiphysics modeling, digital twins and machine learning are positioned.

References:

1. Romanov A.A. Prikladnoi sistemnyi inzhiniring [Applied Systems Engineering]. Moscow, FIZMATLIT, 2015.

2. Kondrat’ev V.V. Model’no-orientirovannyi sistemnyi inzhiniring 2.0 [Model-Based Systems Engineering 2.0]. Moscow, MFTI, 2021.

3. Garichev S.N., Gorbachev R.A., Davydenko E.V., Dzhaparov B.A., Kondrat’ev V.V. Model’no-orientirovannyi inzhiniring fiziko-tekhnicheskikh, informatsionnykh i intellektual’nykh system [Model-based Engineering of Physical, Technical, Information and Intelligent Systems]. Trudy MFTI, 2022, vol.

14, no 2.

4. Aleshchenko A.S., Klishev O.P., Kondrat’ev V.V., Rasskazov A.A. Sovmeshchenie arkhitekturnykh i matematicheskikh modelei v sistemnom inzhiniringe tekhnicheskikh system [Combination of Architectural and Mathematical Models in System Engineering of Technical Systems]. Kosmonavtika i raketostroenie, 2021, no 5.

5. Potyupkin A.Yu., Chechkin A.V. Iskusstvennyi intellekt. Na baze informatsionno-sistemnoi izbytochnosti [Artificial Intelligence. Based on InformationSystem Redundancy]. Mosc ow, Kurs, 2022.

6. GOST R 57700-37–2021. Komp’yuternye modeli i modelirovanie. Tsifrovye dvoiniki izdeliya. Obshchie polozheniya [GOST R 57700-37–2021. Computer

models and simulation. Digital twins of products. General provisions]. Kodeks. URL: https://docs.cntd.ru/document/1200180928

7. Borovkov A.I., Burdakov S.F., Klyavin O.I., et al. Komp’yuternyi inzhiniring [Computer Engineering]. Ucheb. posobie. Saint Petersburg, Izd-vo Politekhn.

un-ta, 2012.

8. Peredovye proizvodstvennye tekhnologii: vozmozhnosti dlya Rossii. Ekspertno-analiticheskii doklad: Monografiya [Advanced Manufacturing Technologies: Opportunities for Russia. Expert Analytical Report: Monograph]. Pod red. A.I. Borovkova. Saint Petersburg, Politekh-Press, 2020.