Abstract
The article formulates directions and analyzes the possibilities of substantiating and choosing the most optimal variant of applying mathematical models for forecasting the number and range of spare parts. The provided recommendations allow to take into account the multi-brand fleets of motor transport enterprises and trends for extrapolation in the short term, identified by the results of observations in real operating conditions. The main reasons for the occurrence of prolonged vehicle downtime due to technical malfunctions are considered. Traditional methods of planning spare parts inventories based on the use of reliability theory and results of mileage forecasting, standard time to failure; inventory management theory and statistical methods for forecasting random processes; methods of operations research; economic and mathematical methods; stochastic methods of transformation of random variables are analyzed. The article formalizes the grouping of factors that affect the size of stocks and the range of spare parts in the operation of rolling stock of enterprises, depending on the state of the system of organization of work of services for maintenance and repair of vehicles; structure of the fleet and technical characteristics of vehicles; level of development of the production base; availability, interest and qualification of personnel; operating conditions of automotive equipment. It is proposed to improve the logistics of spare parts inventory management and to formulate measures to improve the performance of carriers based on an assessment of the total costs incurred by the enterprise to maintain the reliability of rolling stock in operation and taking into account the amount of lost profit due to vehicle downtime in the technical service units. At the same time, it is recommended to use the mathematical apparatus of fuzzy set theory for decision-making, which allows formalizing the parameters of vaguely defined expectations of consumers of motor transport services and reducing the subjectivity of decision-making when solving problems of optimizing spare parts stocks in the transport process management system based on the analysis of the structure of consumer properties and service quality indicators.
Published Version
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