| When systems possess components with wearout failure characteristics, that is when the hazard rates that are not constant, and in the presence of standby redundancy configurations, the most common method currently utilized in industry for handling the reliability predictions of such systems are based on Monte Carlo Simulations. Monte Carlo Simulations are relatively easy to develop, but accuracy of the approximations that are produced is dependant on number of simulation trials and selected seed. To obtain high accuracy for moderately complex system reliability models, Monte Carlo Simulation based system reliability models need to be run for greater than 10,000 trials to achieve accuracy to the 5th or 6th decimal, which is sometimes required for Department of Defense (DoD) contracts in the aerospace industry. Markov Analysis is an alternate approach for modeling system reliability which produces higher accuracy results than Monte Carlo Simulation based modeling, and requires fewer iterations. |
