DOI: 10.18503/1995-2732-2021-19-2-98-102
Abstract
Metallurgical enterprises are a combination of various technical systems that operate in severe and super heavy duty modes. At the same time, many of these technical systems are unique, costly to manufacture and operate, and operate outside the warranty period. The failure of such systems, and even more so their accidents, may lead to irreparable losses, human casualties, loss of profits by the enterprise. Insufficient attention is paid to assessing the quality of technical systems of metallurgical enterprises from the standpoint of reliability and safety, therefore, the presented paper has a sufficient degree of relevance. The study basically contains a structural risk analysis. The novelty is highlighted in the creation of a scientific and methodological base for assessing the quality of technical systems of a metallurgical enterprise as the likelihood of their trouble-free and reliable operation. The paper describes the proposed mathematical models and calculated quantitative indicators of an accident risk for 15 cranes of the basic oxygen furnace shop of a metallurgical enterprise. The obtained indicators are in satisfactory agreement with the known actual data, indicating adequacy and correctness of this approach. This approach was first applied for the metallurgical industry, which indicates the prospects for its development and application. The designated scientific and methodological base is the basis for the creation of digital twins for diagnostics and monitoring of the actual technical state of the technical systems under study. Changes in the properties of system elements lead to a change in the probabilities of their failures and accidents. Using the proposed approach, we will build probabilistic models for a technical system (cranes), a group of systems (a shop), a complex system (a metallurgical enterprise), connecting their properties and the probability of their failure leading to an accident. The properties of such systems change over time. Diagnostics and monitoring are applied to record these changes. To predict changes in technical systems, we will use the probability density function of loading cycles, acting stresses, and deformations.
Keywords
Quality, safety, risk criteria, structural risk analysis, quantitative risk assessment, probability, probabilistic modeling, technical system, scientific and methodological base, digital twin
For citation
Izvekov Yu.A. Scientific and Methodological Base for Assessing the Quality of Technical Systems of a Metallurgical Enterprise. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2021, vol. 19, no. 2, pp. 98–102. https://doi.org/10.18503/1995-2732-2021-19-2-98-102
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