determination of a model of preventive maintenance of special purpose vehicles

Introduction/purpose: the aim of this paper is to obtain quantitative and qualitative indicators of vehicle condition and reliability based on operational data which can be used to determine the optimal periodicity of preventive maintenance for special purpose vehicles, and to more accurately manage the maintenance process and the operational readiness of these vehicles. methods: based on operational failure data and statistical methods, a mathematical model of the reliability of special purpose vehicles was determined. using this model and operational data, the periodicity of preventive maintenance for the vehicles was determined through multicriteria optimization, considering both readiness and minimum maintenance costs. the same methodology was applied to determine the optimal preventive maintenance periodicity for 15 components of the mechanical system of special purpose vehicles. a group analysis was conducted using minitab 15 statistical software, based on the theory of similarity in preventive maintenance periodicity for the 15 components, and a statistical analysis of the conducted research was performed using minitab 16 statistical software. results: models for preventive maintenance of special purpose vehicles were developed based on the recorded vehicle failures and the failures of fifteen vital components. a group analysis grouped the fifteen components into optimal maintenance groups, similar in terms of working time between failures. the statistical analysis of the research determined a functional relationship for the optimal periodicity of preventive maintenance for special purpose vehicles. conclusion: the maintenance periodicity obtained through multi-criteria analysis is optimal, as it achieves satisfactory vehicle readiness with optimal maintenance costs. the statistical analysis of the research concluded that the maintenance periodicities of the vehicle components are different. in both fleets, the engine and the transmission block have the longest maintenance intervals. the research results can be used to rationalize the existing preventive maintenance concept.