Intelligent monitoring and predictive maintenance technologies in the railway transportation process management system

Abstract

The article discusses modern approaches to ensuring the safety and efficiency of interaction between
railway transport systems through the digitalization of technological processes and the implementation
of intelligent monitoring and diagnostic subsystems. An analysis of the existing types of maintenance for
transport infrastructure facilities is carried out, including preventive maintenance, condition-based
maintenance, and predictive maintenance. The necessity of transitioning to a predictive model of
transportation process management based on monitoring data processing and forecasting the technical
condition of facilities is substantiated. The concept of a “smart railway station” integrating transportation,
diagnostics, monitoring, and cargo parameter control processes into a unified digital management
environment is proposed. Particular attention is paid to the implementation of automated weighing
systems and the development of a program for intelligent control of wagon weight parameters at the
Zavodskaya station of a metallurgical plant. The program provides digital support of wagons throughout
the technological chain, intelligent verification of cargo weight data, and decision-making regarding the
necessity of repeated weighing based on the analysis of previously obtained information. The research
results demonstrate that the use of digital monitoring and intelligent control technologies makes it
possible to reduce the number of repeated wagon weighings, decrease shunting operations and wagon
idle time, improve the reliability of cargo information, reduce the influence of the human factor, and
enhance train traffic safety. The proposed approach forms the basis of a predictive management model
for the transport complex focused on failure prevention and optimization of operational processes.