Copula-Based Reliability Analysis of Vehicles Based on Censored Failures Data Using Reliability Importance Measures

The reliability of modern vehicles is a current research problem described in many scientific publications. Currently, the literature includes studies on the reliability of vehicles as technical objects, focusing on the one-dimensional domain of the reliability function. However, failures are the result of the wear and aging of the vehicle components, which should be considered in terms of the operation time of operation and the amount of work performed. Therefore, this paper aims to develop a novel two-dimensional copula-based reliability model with respect to vehicle operating time and mileage. The relationship between the two dimensions was determined to be monotonic using Kendall's tau. The vehicle was considered as a series system consisting of seven main subsystems with independent failure processes. The marginal cumulative distribution functions of time and mileage between failures were estimated on the empirical data. The best-fitted approximated marginal distributions were chosen based on the Cramer-von Mises statistics. Weak links in the reliability structure were identified using modified Birnbaum, criticality, and Barlow-Proschan importance measures. The most failing subsystems turned out to be: the engine, transmission system, and electrical installation.