Article

Received 19.03.2025

Revised 14.05.2025

Accepted 28.06.2025

Retrieved from Vol. 29, No. 1, 2025

Pages 3 -11

Andrusenko, S., Biletskyi, V., Buhaichuk , O., & Podpisnov, V. (2025). Cost-effectiveness of remote monitoring and predictive maintenance of the fleet. The National Transport University Bulletin, 29(1), 3-11. https://doi.org/10.33744/2308-6645-2025-1-60-003-011

Cost-effectiveness of remote monitoring and predictive maintenance of the fleet

Serhii Andrusenko Volodymyr Biletskyi Oleksandr Buhaichuk Vladyslav Podpisnov

The article examines the economic prerequisites and potential advantages of system implementation remote monitoring of commercial vehicles in terms of efficiency gains operation and optimization of maintenance costs. Modern approaches to vehicle maintenance, in particular the limitation of traditional methods of routine preventive and routine maintenance. Emphasis is placed on digital capabilities monitoring technologies that provide operational diagnostics, decision support and implementation of predictive service strategies, which allows for significant reduction downtime and repair costs. Comparative analysis of traditional service models and approaches based on use of telemetry data and analytics. A generalized cost analysis model is proposed and benefits (cost-benefit analysis), which includes key performance indicators such as level use of equipment, service intervals and return on investment (ROI). Implementation problems, in particular those relating to initial investment, were dealt with separately infrastructure support and staff training. It was concluded that the integration of remote monitoring systems contributes not only to improving the technical reliability and safety of the fleet, as well as improving the overall economic performance indicators of transport enterprises. The proposed methodical approach can be it is used in both small and large automobile farms and serves as a basis for strategic ones planning and digital transformation in the field of transport

automobile transport; remote monitoring; predictive maintenance; operational efficiency; cost optimisation; investment profitability

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https://doi.org/10.33744/2308-6645-2025-1-60-003-011