Abstract

When planning daily shifts in a motor transport enterprise, the main task is to maximize the use of the vehicle fleet’s carrying capacity, estimated by the amount of cargo that can be transported per shift (day) in the absence of all types of unproductive losses. The solution to this problem can be found within the framework of the concept of lean thinking, the center of which is the identification and elimination of unproductive losses. To identify the factors that caused losses, causal research is used, an example of which, along with others, is the situational approach. The problematic situation is a cause-and-effect complex of factors, the elimination of which ensures an increase in the efficiency of cargo transportation. The situation model contains a quantitative assessment of the goal of eliminating the problem situation, technical and operational indicators characterizing certain types of losses and recommended measures to eliminate them. The purpose of the study is to develop tools for assessing losses in the carrying capacity of a vehicle fleet, based on situational modeling in the implementation of the principles of lean thinking in relation to the transportation of metallurgical cargo. The study used methods of situational analysis, mathematical modeling, and analysis of technical and operational indicators of the transport process. To study the state of the issue, an analysis of scientific literature was carried out. The main results of scientific novelty are: a situational model of vehicle fleet capacity losses; coefficients of loss of vehicle fleet carrying capacity when transporting metallurgical cargo. Calculation of vehicle fleet capacity loss coefficients must be made using the capabilities of intelligent navigation control systems. Further research is expected to be conducted in the direction of developing specific applications of the concept of lean thinking and situational approach to increasing the efficiency of cargo transportation, as well as in the direction of developing digital systems for managing road transport.

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