MAINTENANCE AND REPAIR OF MEDICAL EQUIPMENT IN CONDITIONS OF LIMITED RESOURCES
- Authors: Ivaschenko A.V.1, Mashkov K.K.2
-
Affiliations:
- Samara State Medical University
- Penza State Technological University
- Issue: No 3 (2025)
- Pages: 102-112
- Section: MODELS, SYSTEMS, MECHANISMS IN THE TECHNIQUE
- URL: https://bakhtiniada.ru/2227-8486/article/view/360416
- DOI: https://doi.org/10.21685/2227-8486-2025-3-8
- ID: 360416
Cite item
Full Text
Abstract
Background. The paper discusses the urgent problem of organizing the maintenance and repair of modern medical equipment in conditions of low availability of components and spare parts and limited resource. Materials and methods. For the first time, a decomposed resource model is proposed and the experience of its practical use for organizing the maintenance and repair of medical equipment is presented, taking into account modern requirements and operating conditions. The decomposed resource model is based on the hierarchical decomposition of a unit of medical equipment (device) into components according to the criterion of autonomy and frequency of maintenance and repair. Autonomy means the feasibility of separate maintenance and repair of components taking into account the requirements of reliability and safety of the equipment. The requirement of necessity and sufficiency of maintenance of a unit of medical equipment is determined in the form of the requirement of unity of coverage of events of maintenance and repair of its components. Results. It is proposed to use the proposed decomposed resource model in solving the problem of managing maintenance and repair during the transition from planning according to regulations to planning by resource. The developed model of the decomposed resource was implemented in planning the maintenance and repair of some types of medical equipment in the clinics of the Samara State Medical University for cases where scheduled provision of spare parts and components is impossible. Conclusions. The proposed model of the decomposed resource allows implementing adaptive methods for planning and managing the maintenance and repair of medical equipment in decision support systems for the operation of equipment with a limited resource.
About the authors
Anton V. Ivaschenko
Samara State Medical University
Author for correspondence.
Email: anton.ivashenko@gmail.com
Doctor of technical sciences, professor, head of the Higher school of medical engineering
(89 Chapayevskaya street, Samara, Russia)Kirill K. Mashkov
Penza State Technological University
Email: k.k.mashkov@samsmu.ru
Postgraduate student
(1A Baidukova street, Penza, Russia)References
- Jiang X., Hu Z., Wang S., Zhang Y. Deep learning for medical image-based cancer diagnosis. Cancers. 2023;15(14):3608.
- Ganus Yu.A., Porfiriev A.S. Theoretical foundations of integrated logistics support modeling. Ekonomika vysokotekhnologichnykh proizvodstv = Economics of high-tech industries. 2023;4(1):51–72. (In Russ). doi: 10.18334/evp.4.1.119518
- Morozov A.I., Rykov V.V. Maintenance and repair of medical equipment. Moscow: Meditsina. 2018:328. (In Russ)
- Bolieva M.V. The problem of import substitution of medical equipment and its consumables for functional research methods. in cardiology. Internauka = Internauka. 2022;(46-5):56–57. (In Russ)
- Istomina T.V. The current state and prospects of using information communication technologies in Russian medicine. Meditsinskaya tekhnika = Medical technology. 2021;(1):30–33. (In Russ)
- Shelekhov P.V., Omelyanovsky V.V. Analysis of the fleet of X-ray equipment in the Russian Federation. Meditsinskie tekhnologii. Otsenka i vybor = Medical technologies. Evaluation and selection. 2023;(3):26–32. (In Russ). doi: 10.17116/medtech20234503126
- Basova L.A., Martynova N.A., Kochorova L.V. Problems of reliability in medical and technical practice. Zdravookhranenie = Healthcare. 2014;(1):106–112. (In Russ)
- Sidorov I.V. Maintenance of medical equipment: problems and prospects. Meditsinskaya tekhnika = Medical equipment. 2019;(4):3–8. (In Russ)
- Nesterova E.V., Igrunova S.V., Grigorenko I.N. et al. Automation of fault prediction of medical equipment. Avtomatizatsiya i modelirovanie v proektirovanii i upravlenii = Automation and modeling in design and management. 2024;(3):13–22. (In Russ). doi: 10.30987/2658-6436-2024-3-13-22
- Wang Kwong Sai, Shcherbakov M.V. A method for predicting the residual resource based on data processing of multi-object complex systems. Prikaspijskij zhurnal: upravlenie i vysokie tekhnologii = Caspian Journal: management and High Technologies. 2019;1:33–44. (In Russ)
- Yurtsev E.S., Savinov Yu.I., Kulikova D.V., Zhigar A.N. Modern diagnostic methods for complex technical systems in digital production conditions. Stankoinstrument = Machine tools. 2020;(2):64–71. (In Russ)
- Pravda O.Yu., Yarotskaya N.A. The influence of high-precision diagnostics of equipment condition on the economy of industrial enterprises. Stankoinstrument = Machine tools. 2022;(2):78–81. (In Russ)
- Postnikova E.S., Yarotskaya N.A., Sidorov I.M., Koshevoy A.R. Methods of determining time for maintenance and repair of machining equipment. Izvestiya Tulʹskogo gosudarstvennogo universiteta. Tekhnicheskie nauki = Proceedings of Tula State University. Technical sciences. 2024;(9):96–101. (In Russ). doi: 10.24412/2071-6168-2024-9-96-97
- Nasonov M.A., Reshetnikov I.S. Architectural transformation of the system of technical maintenance of equipment in industrial production. Avtomatizatsiya v promyshlennosti = Automation in industry. 2025;(3):3–11. (In Russ)
- Yang L., Chen Y., Ma X. et al. A prognosis-centered intelligent maintenance optimization framework under uncertain failure threshold. IEEE Transactions on Reliability. 2024;73(1):115–130.
- Cummins L., Sommers A., Ramezani S.B. et al. Explainable predictive maintenance: a survey of current methods, challenges and opportunities. IEEE Access. 2024;12:57574– 57602.
- Yahya A.A. Improving models of predictive diagnostics and assessment of the condition of transformer equipment of power facilities: PhD dissertation. (In Russ)
- Polyakov A.A., Chikhladze Z.D., Umnov P.I. Predictive analysis in the foresight of MRO. Aktualʹnye voprosy sovremennoj nauki i obrazovaniya: sb. st. X Mezhdunar. nauch.-prakt. konf. (Penza, 20 maya 2021 g.) = Actual issues of modern science and education: collection of art. X International Scientific and Practical Conference (Penza, May 20, 2021). Penza: Nauka i Prosveshchenie, 2021;(1):40–43. (In Russ)
- Dolgov O.S., Safoklov B.B. Designing an aircraft maintenance and repair model using artificial neural networks. Vestnik Moskovskogo aviatsionnogo instituta = Bulletin of the Moscow Aviation Institute. 2022;29(1):19–26. (In Russ). doi: 10.34759/vst-2022- 1-19-26
- Taillard É.D. Decomposition methods. in: design of heuristic algorithms for hard optimization. Graduate Texts in Operations Research. Springer, Cham. 2023:131–152. doi: 10.1007/978-3-031-13714-3_6
- Nadkarni P.M. Metadata-driven software systems in biomedicine: designing systems that can adapt to changing knowledge. Springer Science & Business Media, 2011:72.
Supplementary files













