Reduction of complex safety models based on Markov chains

Abstract

This paper presents a method how to reduce safety models based on Markov chains. The safety model is used to calculate the probability and rate of an event leading to the hazard state - situation, where safety of a modeled system is violated, so the system may cause material loss or mortality. The reduction method allows us to prove that the rate of the event is sufficiently small hence the hazard state may be neglected. The real safety model of railway station signaling and interlocking equipments is used as a case study.