Predicting the Life Expectancy of Railway Fail-Safe Signaling Systems Using Dynamic Models with Censoring

In the presented work we predict the life expectancy of multi-part railway fail-safe signaling systems. The monitored electronic track circuits detect train locations and movement in real time, and issue alerts and warnings to prevent collisions. Based on 10 years of failure reports from the manufacturer of systems used by Railway Infrastructure Administration in the Czech Republic, we establish estimates of time-to-failure distributions of their components. We modify and apply survival models for censored data with various parameters for which we propose and compare new estimators. Both left and right time-based censoring of the data is considered. This approach allows us to include in the analysis components that were in operation before the study started, as well as components that were functional after the end of the study. Special attention is paid to the correct treatment of missing and incomplete data in the analyzed reports. We compare models with constant and variable failure rates. Hypotheses testing methodology is used to select a model with the best fit for the analyzed data.