Reliability of Redundant M-Out-Of-N Architectures With Dependent Components: A Comprehensible Approach With Monte Carlo Simulation

TL;DR

This paper analyzes how component dependencies affect the reliability of M-out-of-N redundant systems using Monte Carlo simulation, revealing nonlinear effects and providing an online tool for tailored reliability assessment.

Contribution

It introduces three dependency models and evaluates their impact on system reliability, offering a comprehensive approach with an accessible simulation platform.

Findings

Interdependencies degrade reliability of parallel systems

Serial systems' reliability can be improved by dependencies

Intermediate configurations show mixed reliability effects

Abstract

Redundant architectures can improve the reliability of complex systems. However, component dependencies can affect the architecture and negate the benefit of redundancy. In this paper, we develop three component dependency models and analyze the reliability of different M-out-of-N configurations using Monte Carlo simulation. The first model assumes a linear component dependency. The second and third models consider common cause failures, in the latter for all components and in the second for random groups of components. As expected, the results show that interdependency degrades the reliability of parallel 1ooN systems while improving it for serial NooN systems. Interestingly, 2oo3 systems produce intermediate results that show an improvement in reliability for certain indicators and a deterioration for some others, depending on the type of dependency models. The results show nonlinear properties of MooN systems with dependent components, which suggest careful handling in applications. An online simulation platform based on Monte Carlo Simulation enables product designers to use the models efficiently and achieve tailored results