Abstract

The article is devoted to the study of the life cycle of railway transport services in freight transportation. The features of the service are describe as a type of product. A parametric model of the life cycle of providing services by rail is construct from the moment of loading goods into wagons at the departure station to the moment of unloading at the destination station. There are the comparison of the service life cycle and the turnover of the car. Other operational indicators, features of their calculation and interrelation are also analyze. It is propose to minimize the service life cycle by digitalizing the rationing of operational indicators. It is present the calculation algorithm using by digital methods. The elements of the program interface for calculating and rationing operational indicators are given. The life cycle of the service is comparable to the turnover of the car, but does not take into account the empty mileage of the car. Minimizing the life cycle of products is an important aim, because it will reduce costs, increase the competitiveness and attractiveness of rail transport for cargo owners. Digitalization of the process of calculating and rationing operational indicators can solve this problem.
 Purpose. The purpose is to apply the product life cycle period to the railway transport service during freight transportation with the subsequent search for opportunities to improve the quality of services provided.
 Methodology. The article used the analysis of the provision of transportation services from the standpoint of quality management, modeling, as well as the creation of an algorithm and a program for digitalization of a number of operations.
 Results. The cargo transportation service is differentiate into stages of the life cycle period. It is present a parametric model. They are outline the ways of minimizing the life cycle, which will reduce costs, increase the competitiveness and attractiveness of railway transport for cargo owners. Digitalization of the stage of calculation and rationing of operational indicators can solve this problem
 Practical implications. It is advisable to apply the results obtained in the railway transportation system, in the work of operators and transport and logistics companies, in the management of the car fleet.

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