Ensuring the efficiency of the system of technical maintenance and repair of transport and technological mashines
More details
Hide details
Associate Professor departments of construction, road, reclamation, agricultural machinery and equipment, National University of Water and Environmental Engineering
Associate Professor Department of Industrial Mechanical Engineering, Lutsk National Technical University
Associate Professor Department of Light Industry Technologies, Lutsk National Technical University
Mykola Holotiuk   

Associate Professor departments of construction, road, reclamation, agricultural machinery and equipment, National University of Water and Environmental Engineering
Submission date: 2022-09-26
Final revision date: 2023-02-19
Acceptance date: 2023-03-02
Publication date: 2023-03-31
The Archives of Automotive Engineering – Archiwum Motoryzacji 2023;99(1):5–17
Current situation with the fleet of transport and technological machinery in Ukraine requires an individual approach to evaluating the effectiveness of its maintenance and repair system. The article is devoted to the issue of selecting the most effective option for the use of transport and technological machinery taking into account the specific conditions of its operation characterized by certain risks and uncertainties, and considering the real volumes and age structure of the fleet. Solving this problem requires substantiation of management models of maintenance and repair processes. It is necessary to provide scientifically based methods of managing the system of technical maintenance (TM) and repair of transport and technological machinery (RTTM) using specific methods of an individual approach to the technical and economic evaluation of the effectiveness of maintenance and RTTM processes which are adapted to the modern conditions of its operation. The article presents the results of the research, which was carried out using the basics of system analysis, the theory of decision-making under the conditions of uncertainty, and the basics of multi-criteria analysis. In the course of research, an analytical management model of the maintenance and repair system operation was formed that reveals the sequence of implementing the management methodology, which makes it possible to assess its state in successive discrete states, to promptly take into account the effect of external influencing factors and make corrections, which, in turn, allow increasing the validity of strategic decisions aimed at increasing the effectiveness. A numerical calculation was performed, which allowed us to conclude that the value of maintenance intervals has a significant impact on the indicator of effectiveness. Adjusting this value makes it possible to optimize maintenance and repair processes.
Abakumov G.V., Buzin V.A., Karnaukhov V.N. The influence of season conditions on technical maintenance effort of transport-technological machines. Bulletin of the Kurgan State Agricultural Academy. Technical science. 2015, 4, 33–35.
Алтунин А.Е. Модели и алгоритмы принятия решений в нечетких условиях: [Монография]. Рос. Федерация. М-во образования. Тюм. гос. ун-т. - Тюмень: Изд-во Тюм. гос. ун-та, 2002, 265. (in Russian: Altunin A.E., Semuhin M.V. Models and algorithms for making decisions in fuzzy conditions. Tyumen: Tyumen State University.).
Бутько Т.В., Вовк Р.В., Панченко Н.Г., Рибалко А.П. Елементи теорії ймовірностей і математичної статистики в управлінні процесами перевезень: навч. посіб. Харків, УкрДАЗТ, 2011, 308, (in Ukrainian: Butko T.V., Vovk R.V., Panchenko N.G., Rybalko A.P. Elements of the theory of probabilities and mathematical statistics in the management of transportation processes: study guide. Kharkiv, UkrDAZT).
Chernyaev I., Oleshchenko E., Danilov I.: Methods for continuous monitoring of compliance of vehicles’ technical condition with safety requirements during operation. Transportation Research Procedia. 2020, 50, 77–85, DOI: 10.1016/j.trpro.2020.10.010.
Diaz K., Kammoun M.A., Hajej Z., Sefiani N., Milazzo M.F.: Optimal management of production, maintenance, and logistic activities in multi-site environments. IFAC-PapersOnLine. 2022, 55(10), 1769–1774, DOI: 10.1016/j.ifacol.2022.09.654.
Fishburn P.C. Utility Theory for Decision Making. Wiley, New York, 1970.
Горемикіна Ю. В. Формалізація даних та методичні підходи у контексті оцінки ефективності соціальних послуг. Механізм регулювання економіки. 2012, 1, 188–195, (in Ukrainian: Goremykina Yu.V. Data formalization and methodical approaches in the context of evaluating the effectiveness of social services. Mechanism of economic regulation).
Karelina E., Podgornyy A., Ptitsyn D., Dobromirov V., Kravchenko P.: Solving the multi-criteria problem of choosing a vehicle using analytical models. Transportation Research Procedia. 2021, 57, 270–276, DOI: 10.1016/j.trpro.2021.09.051.
Kotenko I., Saenko I., Ageev S.: Hierarchical fuzzy situational networks for online decision-making: Application to telecommunication systems. Knowledge-Based Systems. 2019, 185, 104935, DOI: 10.1016/j.knosys.2019.104935.
Lotko M.: Measuring and assessment of the quality of motorcar maintenance and repair services with using the SERVQUAL model with regard to customer’s profile. The Archives of Automotive Engineering – Archiwum Motoryzacji. 2017, 77(3), 51–62, DOI: 10.14669/AM.VOL.77.ART4.
Makarova I., Shubenkova K., Buyvol P., Mavrin V., Giyatullin I., Magdin K.: Safety Features of the Transport System in the Transition to Industry 4.0. The Archives of Automotive Engineering – Archiwum Motoryzacji. 2019, 86(4), 79–99, DOI: 10.14669/AM.VOL86.ART6.
Mosadeghi R., Warnken J., Tomlinson R., Nirfenderesk H.: Comparison of Fuzzy-AHP and AHP in a spatial multi-criteria decision making model for urban land-use planning. Computers, Environment and Urban Systems. 2015, 49, 54–65, DOI: 10.1016/j.compenvurbsys.2014.10.001.
Pereira Jr. J.G., Ekel P.Ya., Palhares R.M., Parreiras R.O.: On multicriteria decision making under conditions of uncertainty. Information Sciences. 2015, 324, 44–59, DOI: 10.1016/j.ins.2015.06.013.
Robert E., Berenguer C., Bouvard K., Tedie H., Lesobre R. Joint dynamic scheduling of missions and maintenance for a commercial heavy vehicle: value of on-line information. IFAC-PapersOnLine. 2018, 51(24), 837–842, DOI: 10.1016/j.ifacol.2018.09.672.
Semykina A., Zagorodnii N., Novikov A.: Study of the effectiveness of the organization of the system of maintenance and repair of quarry transport of mining and processing plants. Transportation Research Procedia. 2022, 63, 983–989, DOI: 10.1016/j.trpro.2022.06.097.
Semykina A., Zagorodnii N., Novikov I., Novikov A.: Main directions of improving the maintenance and repair of vehicle units in the Far North. Transportation Research Procedia. 2021, 57, 611–616, DOI: 10.1016/j.trpro.2021.09.090.
Сорока К.О.: Основи теорії систем і системного аналізу: Навч. посібник. Харків: видавн. ХНАМГ. 2004, 291 (in Ukrainian: Soroka K.O.: Basics of systems theory and system analysis: Study. guide. Kharkiv).
Swanson L.: Linking maintenance strategies to performance. International Journal of Production Economics. 2001, 70, 3, 237–244, DOI: 10.1016/S0925-5273(00)00067-0.
Toniolo A., Cerutti F., Norman T.J., Oren N., Allen J.A., Srivastava M., et al.: Human-Machine Collaboration in Intelligence Analysis: An Expert Evaluation. Intelligent Systems with Applications. 2022, 200151, DOI: 10.1016/j.iswa.2022.200151.
Voronin V.: Diagnostic principles in maintenance systems. Transportation Research Procedia. 2022, 63, 2789–2795, DOI: 10.1016/j.trpro.2022.06.323.
Zadeh L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems. 1978, 1, 3–28, DOI: 10.1016/0165-0114(78)90029-5.
Declaration of availability