Abstract
In this article, we consider two Markov models with standbys and imperfect coverage for the performance prediction of a repairable redundant system. Model I deals with a redundant system comprising one operating unit and one standby unit. In model II, some realistic features such as common cause failure, reboot, and recovery are taken into account to analyze a two-unit system. The reliability and MTTF analyses have been carried out using Laplace transform approach for model I. The availability analysis of the system studied in model II has also been evaluated by implementing the recursive approach. The analytic expressions for predicting the availability and other performance measures of the systems are presented. Furthermore, the numerical results obtained from the analytical expressions are compared with the hybrid soft computing technique based on adaptive neuro-fuzzy inference system (ANFIS).
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Jain, M., Kumar, P. (2019). Availability Prediction of Repairable Fault-Tolerant System with Imperfect Coverage, Reboot, and Common Cause Failure. In: Deep, K., Jain, M., Salhi, S. (eds) Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models . Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-13-0857-4_6
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