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JOURNALS // Russian Journal of Cybernetics // Archive

Russian Journal of Cybernetics, 2025 Volume 6, Issue 1, Pages 116–127 (Mi uk203)

Efficiency of conducting technical inspections on corporate vehicle fleets within limited timeframes

D. V. Fedotova, T. V. Gavrilenkoba

a Surgut State University, Surgut, Russian Federation
b Surgut Branch of Scientific Research Institute for System Analysis of the National Research Centre “Kurchatov Institute”, Surgut, Russian Federation

Abstract: We reviewed modern approaches to monitoring the technical condition of motor vehicles (MV), focusing on risk-based methods. We identified the main problems related to time constraints for inspections, lack of data on previous inspections, and coordination issues between employees. We proposed methods for optimizing inspections, including the use of failure prediction algorithms and automated diagnostic systems. We conducted a comparative analysis of time costs and the efficiency of the proposed solutions. Our conclusions allow enterprises to minimize diagnostic costs, increase the safety of MV operations, and improve production performance.

Keywords: risk-oriented inspection, automated diagnostics, failure prediction, machine learning, diagnostics optimization, digital technologies in motor transport, condition monitoring system.



© Steklov Math. Inst. of RAS, 2025