Abstract
The paper considers a new approach to planning and forming a stock of spare parts necessary for the smooth functioning of transport enterprises. The basis of the author's approach is the developed simulation model of the warehouse adapted for any type of enterprise that serves and (or) operates road transport. The need for spare parts in this model is defined as a mixture of probability distributions of demand of various kinds, which makes it universal. The model was based on the new patterns of influence of following factors on the size of the stock revealed by the authors: the statistical indicators of the need for spare parts, the type and location of the enterprise, the target level of reliability of the supply system, etc. The proposed approach allows connecting the main indicators of the resource management effectiveness: the shortage rate, the cost of stock, the level of system reliability. It allows planning and forming a stock of spare parts reasonably. It is expected that the proposed approach will increase the efficiency of transport enterprises and the degree of satisfaction of consumers of their services.
Highlights
The main reason that does not allow solving the task of managing warehouses of spare car parts is an open question of forecasting demand for them
The analysis of numerous data showed that the consumption of spare parts in enterprises serving or operating road transport in most cases cannot be described using known distribution laws of random variables
For the values of the management effectiveness indicators obtained during the simulation, a (100-2α)-percent confidence interval is determined, where α is the level of significance
Summary
The main reason that does not allow solving the task of managing warehouses of spare car parts is an open question of forecasting demand for them. The analysis of numerous data showed that the consumption of spare parts in enterprises serving or operating road transport in most cases cannot be described using known distribution laws of random variables. Having received quantitative estimates of demand, it remains to determine how much and when to order spare parts for the warehouse in order to always have the optimal stock size. This optimization problem would successfully solve the revealed functional dependence between the efficiency indicators of warehouse management: the average size of the warehouse stock and the level of service. It would make it possible to determine the necessary stock sizes to achieve the required level of service without recourse to complex calculations or modeling [5]
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