Robust management and assessment of the stability of production systems

The relevance of the problem of robust management and robust assessments of production systems is due to the need to ensure the competitiveness of manufactured products and the quality of the systems themselves. This, in turn, requires the development of methods to improve the efficiency of the implementation of fiber-optic smart systems based on the assessment of stability and robustness. It is supposed to solve such problems as the development of parameters of a fiber-optic smart system, as well as methods for adapting the robustness model to the assessment of the stability of systems. The solution of the tasks involves the use of methods used in the system analysis of the properties of dynamic systems and new materials, the organization of production, the evaluation of systems based on new materials, taking into account volatility and robustness. The article pays attention to various modes of the dynamic state of the production system, which correspond to certain classifications of robustness. The characteristic of the fiber-optic Smart system model is given from the point of view of the formation of a system unit. The importance of a robust approach for approximating a complex production system to targeted indicators is shown. Special attention is paid to the algorithm for improving the efficiency of the introduction of new materials and technologies. The characteristic of the implementation parameters with a robust approach is presented. At the end of the article, it is proposed to use robust estimators to assess the stability of production systems, and the sequence of their calculation is also presented

Keywords: robust stability, robust quality, robust approaches, fiber-optic systems, new materials and technologies, robust estimators

References

  1. A. A. Bobtsov. Adaptive and robust control of undefined output systems. SPb.: Science, 2011. 174 p.
  2. Fibrous composite materials/Ed. S. Z. Boxtey. Moscow: Mir, 1967. 13 p.
  3. I. V. Miroshnik, V. O. Nikiforov, A. L. Fradkov. Nonlinear and adaptive control of complex dynamic systems. SPb: Science, 2000.
  4. V. O. Nikiforov. Adaptive and robust management with perturbation compensation. SPb: Science, 2003.
  5. General Standard for Design of Printed Circuit Boards/Translation into Russian, Edition 10.2008. https://mp36c.ru/pdf/library/gost/pcb/IPC-2221A-10.pdf.
  6. R. O. Omors. Robustness of interval dynamic systems. Bishkek: Ilim, 2018. P. 104.
  7. M. A. Sivak. Study of the applicability of robast loss functions in neural networks//Collection of scientific works of NGTU. 2020. № 4. P. 50-58.
  8. M. A. Sivak, V. S. Timofeev. Construction of robust neural networks with various loss functions//Data analysis and processing system. 2021. Vol. 82. № 2. P. 67-83.
  9. A. L. Fradkov. Adaptive control in complex systems. M.: Science, 1990.
  10. L. V. Titova, V. V. Ilyinskiy. Substantiation of approaches to the choice of indicators of sustainable development of the microeconomic level//Actual problems of the economy of modern Russia. 2012. № 8. P. 165-168.
  11. L. V. Titova, E. M. Ilyinskaya, M. N. Titova. Concept of robustness in the management of sustainability of textile systems. In the book: Sustainable development of intellectual ecosystems/Ed. A. V. Babkina. St. Petersburg, 2023. P. 144-175.
  12. V. P. Shulenin. Robust methods of mathematical statistics. Tomsk: Izd-vo NTL, 2016. 260 p.
  13. J. T. Barron. A General and Adaptive Robust Loss Function. 2017. https://arxiv.org/abs/1701.03077.

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