Impact of Common Cause Failure on Reliability Prediction of Rail industry

Dependency in systems is one of the problems that reliability faces. Dependence increases the probability of failure and can affect the performance of a system; Therefore, it is very important to study and understand the consequences when designing, operating and maintaining the system. Regardless of the dependency, reliability is optimistically estimated and the system fails sooner than expected. In the rail industry, subsystems show a high level of dependence due to their high dynamics and complexity. Failure of any of the subsystems can affect the performance of the entire network and sometimes have irreparable consequences. Identifying dependencies and dependent failures based on the block diagram of reliability and the structure of the rail system can affect the more accurate prediction of reliability and reduce the subsequent consequences. This paper presents a new mathematical model for predicting reliability in the rail industry by considering common cause failure. Various methods have been introduced to estimate the common cause failure coefficient. The results show an increase in accuracy in predicting reliability.