ИССЛЕДОВАНИЕ ПРОЦЕССА ЭКСПЛУАТАЦИИ И РЕМОНТА ЭЛЕКТРОВОЗОВ С ИСПОЛЬЗОВАНИЕМ ИНСТРУМЕНТОВ BIG DATA И ИМИТАЦИОННОГО МОДЕЛИРОВАНИЯ

Abstract

Objective: To detect random components in the locomotive time budget and assess the efficiency of locomotive operation organization at a testing ground of the railroad. To optimize the system parameters of maintenance and operation of 2ES5K series electric locomotives, according to the factual data of their operation. To compare availability indices before and after the transition to service maintenance. Methods: The methods of probability theory, mathematical statistics, estimation and process-based simulation modeling were applied. Results: A list of typical for locomotive states was revealed in the process of its operation. The matrix of locomotive transitions between its states was built. Theoretical distribution laws and their numerical characteristics were determined for the components of locomotive time budget. It was established, that the types of distribution laws and their numerical characteristics differ before and after the transition to service maintenance. A discrete-event simulation model was developed in the programming environment of AnyLogic, which takes into account the dynamics of the system under examination with initial data variations for the calculation of operation and performance coefficients of locomotives. Practical importance: The simulation of 50 000 000 minutes (about 100 years) duration operating cycle of the locomotive made it possible to conclude, that the transition to service maintenance raises the efficiency of locomotive operation by way of increasing operation and performance coefficients. The designed simulation model may be applied for the solution of other optimization problems, for instance the determination of the required amount of operational fleet locomotives for the specified amount of traffic, the selection of rational sections for regular locomotives and locomotive crews.