Abstract

An efficient simulation algorithm for the quantification of reliability performance indicators of a complex system is demonstrated in the paper that is based on Monte Carlo method. A directed Acyclic Graph is used as a useful system representation. A parallel simulation technique is used in the algorithm which is based on the construction of the special course of life sequence of transformed transition times subjected to the corresponding part of the Acyclic Graph. The parts of the Acyclic Graph represent individual subsystems of a given system and may be effectively evaluated from the reliability point of view. The wide range of models for both deterministic and stochastic processes applied on the terminal nodes of the Acyclic Graph is allowed in the algorithm. The use of the algorithm for comparative theoretical calculations as well as for industrial applications is shown by a visual demonstration. A cost-optimization problem is shortly introduced which may be fully solved by the algorithm using additional genetic algorithms as an applicable optimization technique. The problem takes into account also additional objective that is defined as a prescribed constraint of a selected reliability performance indicator. The solution of the cost-optimization problem is demonstrated on two practical examples.

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