SAFETY ASSESSMENT FOR SAFETY-CRITICAL SYSTEMS USING MARKOV CHAIN MODULAR APPROACH
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Abstract
The Markov Chain Modular (MCM) approach is proposed in this paper in order to solve part of the failure-state dependency problem. The MCM approach completely avoids the failure-state dependency problem by avoiding the combinatorial modeling. To quantitatively assess safety, a new Markov chain modeling technique is developed to represent an m + 2 state homogenous Markov chain model using a three-state Markov model. The transition rate functions of the three-state Markov model can be determined by the transition rates of the m + 2 state Markov chain model. Given a series system has N modules and each module has O(m) operational states, the MCM approach reduces the operational states to O(N × m 2 ) as opposed to O(m 2N ) by using the traditional Markov chain model.