SystemModelReliability

SystemModelReliability[model]

retrieves the lifetime distribution for model.

SystemModelReliability[model,"Components"]

gives a list of components in ReliabilityDistribution or FailureDistribution.

SystemModelReliability[model,"ComponentRules"]

gives a list of translation rules for components.

Details

Examples

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Basic Examples  (3)

Retrieve the lifetime distribution for a model, in this case a ReliabilityDistribution:

Retrieve the lifetime distribution for a model:

Plot the survival function to see the likelihood a system works after a certain time:

Component names from the model are shortened:

Retrieve rules that show the mapping to the original names from the model:

Scope  (3)

Compare the lifetimes between a parallel and a serial system:

Survival functions show a higher probability of functioning for the parallel system at any time:

Compute the expected lifetime for a system:

The expected lifetime is often called the mean time to failure:

Analyze how structurally important components are for system reliability:

Retrieve the original component names:

Looking at system structure, the EMF, inductor and inertia are the most important for reliability:

Applications  (4)

Study the reliability of an electric motor:

Retrieve the lifetime distribution, where the system works if one of the resistors works:

Show the probability of survival over time:

Compute the mean time to failure:

Retrieve the original component names referenced in the ReliabilityDistribution:

Show how structurally important each component is for reliability:

Analyze how important components are for system reliability:

The mean time to failure for this model:

BirnbaumImportance shows that the EMF component is the most important for reliability:

Compare with a model where the EMF component has been improved:

The mean system lifetime has improved around 11%:

Model the reliability of an uninterruptible power supply (UPS) setup:

Power is supplied from the utility through power lines, or from a battery through an inverter:

Compute the mean time to failure (MTTF) and convert it to years:

Compare with a version of the same system with hardened components:

The MTTF for the hardened system is significantly higher:

Compute the two survival functions:

Show the survival functions for the two systems, indicating the different MTTF:

Model how failures impact system performance. A resistor in a DC motor fails at time 20, another at time 35:

One resistor failure decreases motor speed; two failures make the motor fail completely:

Properties & Relations  (1)

Component names are changed when retrieving a system lifetime distribution:

Retrieve the translation rules applied:

Retrieve just the original names, in the same order as referenced in the system distribution:

Wolfram Research (2018), SystemModelReliability, Wolfram Language function, https://reference.wolfram.com/language/ref/SystemModelReliability.html.

Text

Wolfram Research (2018), SystemModelReliability, Wolfram Language function, https://reference.wolfram.com/language/ref/SystemModelReliability.html.

CMS

Wolfram Language. 2018. "SystemModelReliability." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/SystemModelReliability.html.

APA

Wolfram Language. (2018). SystemModelReliability. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/SystemModelReliability.html

BibTeX

@misc{reference.wolfram_2024_systemmodelreliability, author="Wolfram Research", title="{SystemModelReliability}", year="2018", howpublished="\url{https://reference.wolfram.com/language/ref/SystemModelReliability.html}", note=[Accessed: 21-December-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_systemmodelreliability, organization={Wolfram Research}, title={SystemModelReliability}, year={2018}, url={https://reference.wolfram.com/language/ref/SystemModelReliability.html}, note=[Accessed: 21-December-2024 ]}