based on periodic inspection and maintenance data model do prognozowania niezawodności systemu magazynowania w czasie rzeczywistym w oparciu o dane z przeglądów okresowych oraz dane eksploatacyjne

In recent years, storage reliability has attracted much attention for increasing reliability requirement. In this paper, forecast models for real-time reliability of storage system under periodic inspection and maintenance are presented, which is based on the theories of reliability physics and exponential distribution. The models are developed under two newly-defined imperfect repair modes, i.e., Improved As Bad As Old (I-ABAO) and Improved As Good As New (I-AGAN). A completion method for censored life data is also proposed by averaging the residual lifetime. According to the complete and censored lifetime data, parameters in the models are estimated by applying maximum likelihood estimation method and iterative method respectively. A numerical example of a storage system is given to verify the feasibility of the proposed completion method and the effectiveness of the two models.