Reliability & Redundancy Modelling

Failure rate calculation is simple for systems with no redundancies and components with a constant failure rate: simply sum the components’ failure rates.
In these cases, Mean Time Between Failure (MTBF) is also easy to calculate:

 

MTBF=1/Failure Rate

 

However, systems with fault tolerance, redundancies, and components that age (increasing failure rate in time) are harder to model.
Additional details that may affect the system reliability model are: operation profile, spare parts logistics, and scheduled inspections and maintenance.

BQR has vast experience with reliability modeling of complex systems, using BQR’s software tools: Reliability Block Diagram (basic and Networks), Markov chain models, Fault Tree Analysis which supports common causes and nested common causes (common causes within common causes), and apmOptimizer.

BQR also has Monte Carlo simulations that can be adapted to special cases.

BQR advanced tools for reliability modelling

Reliability Block Diagram (Basic)

Used for modelling systems with standard block dependencies (Serial, Parallel, K out of N and Stand-By), with various repair policies (Hot, Cold), and failure distributions.

Reliability Block Diagram (Network)

Used for modelling systems with nonstandard block dependencies.

Monte Carlo Simulations

Used for plotting the point availability and other time dependent parameters.

Markov Chains

Used for modelling load sharing, shared spare parts, and other systems where component failure rate depends on other components.

Fault Tree Analysis

Used mostly for safety analysis, supporting nested common causes.