Decision support system for managing repairs of thermal power equipment
Abstract
Decision support systems in the management of maintenance and repair of complex technical systems equipment are an effective tool for optimizing the costs of enterprises and organizations operating them. Recently, interest in this class of information systems has been growing in the energy sector as well. The paper describes the architecture of the decision support system in the management of repairs of thermal power equipment. The system contains a production knowledge base, which is used to make decisions on the inclusion of a specific unit of power equipment in the repair program. The use of this mathematical apparatus makes it possible to implement a mechanism for explaining the decisions made. A number of classifiers have been developed that allow you to automate the process of compiling a repair program. For convenience, a color interpretation of the results of the evaluation of the technical condition has been implemented. The use of these classifiers as part of a decision support system for compiling repair programs is shown. The description of the ranking of units of power equipment based on the results of the classification, which ensures the qualitative formation of the repair program, is given. The methodological aspects of the application of the developed classifiers and the decision support system are described. The role of the decision maker in the operation of the developed decision support system is shown.
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Protalinskiy O., Andryushin A., Shcherbatov I., Khanova A., Urazaliev N. Strategic decision support in the process of manufacturing systems management. Proceedings of 2018 11th International Conference "Management of Large-Scale System Development", MLSD 2018, 2018. – pp. 8551760.
Sergushicheva M.A., SHvecov A.N. Ierarhicheskaya raspredelennaya sistema podderzhki upravleniya tekhnicheskim obsluzhivaniem i remontom energooborudovaniya // Informacionnye tekhnologii v proektirovanii i proizvodstve: Nauch.-tekhn. zhurn. / FGUP «VIMI», 2009. – №3. – S. 14-19.
Zagorul'ko YU.A., Anureev I.A., Zagorul'ko G.B. Podhod k razrabotke sistemy podderzhki prinyatiya reshenij na primere neftegazodobyvayushchego predpriyatiya // Izvestiya Tomskogo politekhnicheskogo universiteta, 2010. – T. 316. – № 5. S. 127-131.
Protalinskij O.M., Hanova A.A., SHCHerbatov I.A., Protalinskij I.O., Kladov O.N., Urazaliev N.S., Stepanov P.V. Ontologiya processa upravleniya remontami v elektrosetevoj kompanii // Vestnik MEI, 2018. – № 6. – S. 110-119.
Massel' L.V., Vorozhcova T.N., Pyatkova N.I. Ontologicheskij inzhiniring dlya podderzhki prinyatiya strategicheskih reshenij v energetike // Ontologiya proektirovaniya, 2017. – T. 7. – № 1 (23). – S. 66-76.
Pahtusov S.V., Evdakimov I.I., Avramov M.V. i dr. Ekspertnaya sistema diagnostiki neispravnostej gazoperekachivayushchih agregatov na kompressornyh stanciyah // Intellektual'nye sistemy v proizvodstve, 2017. – T. 15. – № 1. – S. 20-25.
Gavrilyuk E.A., Maslov A.O., Pyarin A.R. Metod podderzhki prinyatiya reshenij pri upravlenii diagnostirovaniem, tekhnicheskim obsluzhivaniem i remontom oborudovaniya na primere sistem kontrolya vibracii gazoperekachivayushchih agregatov // Gazovaya promyshlennost', 2018. – №3 (773) – S. 114-125.
Sistemy upravleniya tekhnicheskim obsluzhivaniem i remontom (SU TOiR). URL: https://soware.ru/categories/maintenance-management-systems (date: 27.11.2022).
Protalinskij O.M., Protalinskaya YU.O., Protalinskij I.O., SHCHerbatov I.A., Kladov O.N. Sistema upravleniya proizvodstvennymi aktivami predpriyatij energetiki EAM Optima // Avtomatizaciya i IT v energetike, 2018. – № 9 (110). – S. 24-26.
Protalinskij O.M., SHCHerbatov I.A., Hanova A.A., Protalinskij I.O. Adaptivnaya sistema prognozirovaniya nadezhnosti tekhnologicheskogo oborudovaniya ob"ektov energetiki // Informatika i sistemy upravleniya, 2019. – № 1 (59). – S. 93-105.
Voropai R., Shcherbatov I., Agibalov V., Belov M. Repair program formation on the basis of the technical condition classifiers // Studies in Systems, Decision and Control, 2021. – Т. 342. – pp. 107-116.
Shtovba S.D. Designing fuzzy systems using MATLAB. — M. : Goryachaya liniya. — Telekom, 2007. — 288 p.
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