Propagated failure analysis for non-repairable systems considering both global and selective effects

This paper proposes an algorithm for the reliability analysis of non-repairable binary systems subject to competing failure propagation and failure isolation events with both global and selective failure effects. A propagated failure that originates from a system component causes extensive damage to the rest of the system. Global effect happens when the propagated failure causes the entire system to fail; whereas selective effect happens when the propagated failure causes only failure of a subset of system components. In both cases, the failure propagation that originates from some system components (referred to as dependent components) can be isolated because of functional dependence between the dependent components and a component that prevents the failure propagation (trigger components) when the failure of the trigger component happens before the occurrence of the propagated failure. Most existing studies focus on the analysis of propagated failures with global effect. However, in many cases, propagated failures affect only a subset of system components not the entire system. Existing approaches for analyzing propagated failures with selective effect are limited to series-parallel systems. This paper proposes a combinatorial method for the propagated failure analysis considering both global and selective effects as well as the competition with the failure isolation in the time domain. The proposed method is not limited to series-parallel systems and has no limitation on the type of time-to-failure distributions for the system components. The method is verified using the Markov-based method. An example of computer memory systems is analyzed to demonstrate the application of the proposed method.