Software implementation of the technogenic risk assessment method of an industrial object using the monte-carlo method

Authors

DOI:

https://doi.org/10.15587/2312-8372.2020.200384

Keywords:

technological risk, Monte Carlo method, reliability theory, software package, system reliability.

Abstract

The object of research is the industrial risk of an industrial facility. One of the most problematic places is the uncertainty of the initial information regarding the object of study and the lack of a universal methodology that would allow an assessment of technological risks at all stages of the operation of an industrial object. A particularly acute problem concerns potentially hazardous industries.

The analysis of existing methods and approaches to assessing the technological risks of industrial facilities at different stages of their functioning is carried out. It is established that one of the best methods is the Monte Carlo method, which allows to quantify the uncertainty of decisions. The use of the Monte Carlo method for quantitative hazard analysis in order to determine the probability of accidents and accidents, the magnitude of the risk, the magnitude of the possible consequences is justified.

The elements of the theory of reliability for the quantitative assessment of risks are used. A quantitative hazard analysis in accordance with the theory of reliability makes it possible to determine the probability of accidents and accidents, the magnitude of the risk, the magnitude of the possible consequences. Probability methods and statistical analysis are integral parts of the quantitative analysis of hazards and technological risk.

An algorithm is developed to determine the industrial risk of an industrial facility using the theory of reliability. A software package is developed based on the theory of reliability with a combination of Monte Carlo simulation of the system. The developed software package allows to analyze the level of technogenic risk when using various methods of connecting elements of the system, as well as evaluate changes in the reliability of the system when using other components. The program is presented on the example of a system, the components of which are the heaters PVT1-7 (Ukraine) in the technological system of a thermal power plant. The system under study is at the border of an unacceptable and conditionally acceptable level of danger, which gives grounds for the need to take measures to increase the reliability of the system by increasing the number of backup system elements, or improving their quality.

Author Biographies

Tetyana Bojko, National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», 37, Peremohy ave., Kyiv, Ukraine, 03056

PhD, Associate Professor

Department of Cybernetics of Chemical Technology Processes

Alla Abramova, National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», 37, Peremogy ave., Kyiv, Ukraine, 03056

PhD, Associate Professor

Department of Cybernetics of Chemical Technology Processes

Denys Skladannyy, National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», 37, Peremogy ave., Kyiv, Ukraine, 03056

PhD, Associate Professor

Department of Cybernetics of Chemical Technology Processes

Petro Vavulin, Foreign Enterprise «I-AR-SI», 18A, M. Vovchka str., Kyiv, Ukraine, 04073

Consultant on Information and Telecommunication Technologies

References

  1. Metodyka vyznachennia ryzykiv ta yikh pryiniatnykh rivniv dlia deklaruvannia bezpeky obiektiv pidvyshchenoi nebezpeky (2002). Ministerstvo pratsi ta sotsialnoi polityky Ukrainy No. 637. 04.12.2002. Available at: https://zakononline.com.ua/documents/show/34982___34982
  2. Normatyvy porohovykh mas nebezpechnykh rechovyn dlia identyfikatsii obiektiv pidvyshchenoi nebezpeky (2002). DNAOP 0.00-3.07-02. Kabinet Ministriv Ukrain No. 956. 11.07.2002. Available at: https://zakon.rada.gov.ua/laws/show/956-2002-%D0%BF
  3. Vorobev, Iu. L. (2000). Natsionalnaia bezopasnost i upravlenie strategicheskimi riskami v Rossii. Problemy bezopasnosti pri chrezvychainykh situatsiiakh, 5, 6–15.
  4. Kuhta, A. I. (2019). Integrated method of occupational risk degree assessment at the enterprise. Safety of technogenic and natural systems, 1, 18–27. doi: https://doi.org/10.23947/2541-9129-2019-1-18-27
  5. Raj Pradeesh, T., Venkumar, P., Saravanamani, M. (2019). Hazard Identification using Risk Assesment for A Tyre Manufacturing Process. International Journal of Innovative Technology and Exploring Engineering, 9 (2S2), 353–356. doi: http://doi.org/10.35940/ijitee.b1054.1292s219
  6. Fedosov, A. V., Badrtdinova, I. I., Abdrakhmanova, K. N., Velekzhanin, D. Y. (2019). Quantitative assessment of uncertainty of technogenic accidents risk analysis. Oil and Gas Business, 3, 46–66. doi: http://doi.org/10.17122/ogbus-2019-3-46-66
  7. Quin, S., Widera, G. E. O. (1996). Uncertainty Analysis in Quantitative Risk Assessment. Journal of Pressure Vessel Technology, 118 (1), 121–124. doi: http://doi.org/10.1115/1.2842154
  8. Grigorev, V. S. i dr. (1990). Nekotorye aspekty lokalizatsii i likvidatsii avariinykh vybrosov toksichnikh veshchestv. Vesnik vsesoiuznogo khimicheskogo obshchestvava im. D. I. Mendeleeva, 4 (35), 463−468.
  9. Beati, J.,Caira, M. (2004). Benchmarkon Dynamic Reliability An Approach based on Dynamic Event Tree Analysis. University of Rome “La Sapienza”.
  10. Smolich, S.V. Smolich, K.S. (2004). Reshenie gorno-geologicheskikh zadach metodom Monte-Karlo. Chita: ChiTGU, 103.
  11. Alymov, V. T., Tarasova, N. P. (2006). Tekhnogennyi risk: Analiz i otsenka. Moscow: Akademkniga, IKTS, 118.
  12. Boiko, T. V., Vavulin, P. A. (2014). Calculation and analysis of predictable technological risk value of industrial objects in stationary operating conditions. Eastern-European Journal of Enterprise Technologies, 5 (10 (71)), 42–47. doi: http://doi.org/10.15587/1729-4061.2014.27981
  13. Boiko, T. V., Abramova, A. O., Vavulіn, P. A. (2018). A. s. No. 75863 UA. Programnii kompleks RISK 1.2. published: 12.01.2018.
  14. Publichne aktsionerne tovarystvo «Kharkivska TETs-5».Available at: http://www.tec5.kharkov.ua/
  15. Vavulin, P. A., Boiko, T. V. (2016). Analysis of algorithm for estimating distribution functions of random variables for the prediction of technogenic risk. Technology Audit and Production Reserves, 2 (3 (28)), 17–23. doi: http://doi.org/10.15587/2312-8372.2016.66754
  16. Boiko, T. V., Baturynska, I. R. (2013). Definition man-caused risks based on the monte-carlo method. Eastern-European Journal of Enterprise Technologies, 2 (11 (62)), 4–7. Available at: http://journals.uran.ua/eejet/article/view/11721
  17. Bendiuh, V. I. (2005). Systema otsinky tekhnohennoi bezpeky promyslovykh pidpryiemstv: metodolohiia ta alhorytm rozrakhunku. Kyiv, 193.

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Published

2020-03-05

How to Cite

Bojko, T., Abramova, A., Skladannyy, D., & Vavulin, P. (2020). Software implementation of the technogenic risk assessment method of an industrial object using the monte-carlo method. Technology Audit and Production Reserves, 2(2(52), 4–10. https://doi.org/10.15587/2312-8372.2020.200384

Issue

Vol. 2 No. 2(52) (2020): Information and control systems

Section

Information Technologies: Original Research

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Copyright (c) 2020 Tetyana Bojko, Alla Abramova, Denys Skladannyy, Petro Vavulin

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