Advertisement

Structural Risk Analysis as Basis for Quality Control of Metallurgical Systems

  • Yu. A. Izvekov
  • E. M. Gugina
  • V. V. Shemetova
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

The brief review of the quality control system for complex technical systems is given. A generalizing condition for the analysis and control of safety as the basis for quality control of any complex technical system based on the risk theory has been adopted. The technical risk analysis cannot always adequately evaluate the safety of the structure, so the transition from technical risk to the structural risk of complex technical systems is shown. As an example of such systems, it is proposed to investigate cranes casting bridge type, operating in heavy and superheavy operation modes. Four blocks (subsystems) of the first level of structural risk and ten elements of the second level have been singled out. On the basis of the evolving structural risk theory, its meaningful formulation for complex metallurgical systems is given. A model of structural risk coordinated by goals and tasks has been constructed. The evaluation of structural risk as the probability of catastrophic destruction of a group of objects, metallurgical bridge cranes, will allow one to formulate and analytically determine the parameters of their quality control from the position of safety and reliability.

Keywords

Structural risk analysis Technical risk Quality of metallurgical systems Metallurgical bridge cranes Mechanical system Complex technical system 

References

  1. 1.
    Izvekov YuA (2012) Modelirovanie prognozirovaniya riska nesushchikh konstruktsiy kranov metallurgicheskogo proizvodstva (Model operation of prediction of risk of load-bearing frames of cranes of metallurgical production). Curr Probl Mod Sci Tech Educ 70:6–8Google Scholar
  2. 2.
    Izvekov YuA (2013) Risk-analiz oborudovaniya metallurgicheskikh proizvodstv. Podkhod, kontseptsiya, analiz (Risk analysis of an inventory of metallurgical productions. Approach, concept, analysis). Saarbrucken, DeutschlandGoogle Scholar
  3. 3.
    Frolov KV, Makhutov NA (2006) Bezopasnost Rossii. Pravovye, sotsialno-ekonomicheskie i nauchno-tekhnicheskie aspekty (Safety of Russia. Legal, socio-economic, and scientific and technical aspects). In: 4 parts. part 1: the basic concepts of the analysis and regulation of safety. Znanie, MoscowGoogle Scholar
  4. 4.
    Anon (1989) Risk criteria for land use planning in the vicinity of major industrial hazards. U.K. Health and Safety Executive, LondonGoogle Scholar
  5. 5.
    Anon (1993) Risk analysis, perception, management. The Royal Society, LondonGoogle Scholar
  6. 6.
    Bagrov AV, Murtazov AK (2010) Tekhnogennye sistemy i teoriya riska (Technogenic systems and risk theory). Ryazan State University named for S.A. Yesenin, RyazanGoogle Scholar
  7. 7.
    Biryukov MP (1980) Dinamika i prognoziruyushchiy raschet mekhanicheskikh sistem (Dynamics and the predicting calculation of mechanical systems). Vysheyshya shkola, MinskGoogle Scholar
  8. 8.
    Boulding KE (1956) General systems theory—the skeleton of science. Manage Sci 2:197–208CrossRefGoogle Scholar
  9. 9.
    Brushlinsky NN, Hall JR, Sokolov SV, Wagner P (2003) Fire statistics, June 2003. Academy of State Fire Service, MoscowGoogle Scholar
  10. 10.
    Taguchi G (1985) Quality engineering in Japan. Bull Jpn Soc Precis Eng 4:237–242Google Scholar
  11. 11.
    Hammad DB, Shafiq N, Nuruddin MF (2014) Criticality index of building systems using multi-criteria decision analysis technique. MATEC Web Conf EDP Sci 15:01018CrossRefGoogle Scholar
  12. 12.
    Izvekov YuA (2012) Analiz tekhnogennoy bezopasnosti kranovogo khozyaystva Rossii (Analysis of technogenic safety of crane economy of Russia). Mod High Technol 12:18–19Google Scholar
  13. 13.
    Kumamoto H, Henley EJ (1996) Probabilistic risk assessment and management for engineers and scientists. IEEE Press, New YorkGoogle Scholar
  14. 14.
    Lepikhin AM (2000) Risk analysis of designs of potentially dangerous objects on the basis of probability models of mechanics of destruction. Dissertation, RAS, Siberian Office, Institute of Computing Model Operation, KrasnoyarskGoogle Scholar
  15. 15.
    Malinetsky GG, Potapov AB (2000) Sovremennye problemy nelineynoy dinamiki (The modern problems of non-linear dynamics). Editorial of URSS, MoscowGoogle Scholar
  16. 16.
    Sorensen AG (1973) A statistical analysis of product reliability due to random vibration. In: Proceedings of annual reliability and maintainability symposium, PhiladelphiaGoogle Scholar
  17. 17.
    Stepanov VV (2006) Kurs differentsialnykh uravneniy (The course of the differential equations). KomKniga, MoscowGoogle Scholar
  18. 18.
    Bezopasnost truda v promyshlennosti (Safety of work in the industry) (2010). MoscowGoogle Scholar
  19. 19.
    Gilmore R (1993) Catastrophe theory for scientists and engineers. Dover, New YorkzbMATHGoogle Scholar
  20. 20.
    Poston T, Stewart I (1998) Catastrophe: theory and its applications. Dover, New YorkzbMATHGoogle Scholar
  21. 21.
    Prigozhin I, Stengers I (1994) Poryadok iz khaosa. Vremya, khaos, kvant (Order out of chaos. Time, chaos, quantum). Progress, MoscowGoogle Scholar
  22. 22.
    Sanns W (2000) Catastrophe theory with mathematica: a geometric approach. DAV, GermanyGoogle Scholar
  23. 23.
    Saunders PT (1980) An introduction to catastrophe theory. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  24. 24.
    Thompson J, Michael T (1982) Instabilities and catastrophes in science and engineering. Wiley, New YorkCrossRefGoogle Scholar
  25. 25.
    Izvekov YuA, Kobelkova EV, Loseva NA, Dubrovsky VV, Khamutskikh EYu (2015) Mathematical evaluation of mechanical construction safe loading. J Ind Pollut Control 1:115–118Google Scholar
  26. 26.
    Gugina EM (2017) Raschet nadezhnosti mostovykh kranov metodom preobrazovaniya veroyatnostey (Calculation of reliability of bridge cranes by method of transformation of probabilities). In: Technical sciences: problems and prospects. Materials of the fifth international scientific conference, St. Petersburg, July 2017. Svoyo izdatelstvo, St. Petersburg, pp 68–70Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yu. A. Izvekov
    • 1
  • E. M. Gugina
    • 1
  • V. V. Shemetova
    • 1
  1. 1.Nosov Magnitogorsk State Technical UniversityMagnitogorskRussia

Personalised recommendations