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The Reliability Modeling Toolkit (RMT) is an R-based library of educational tools specifically designed to execute computationally involved and challenging reliability modeling and analytical calculations.

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Center-for-Risk-and-Reliability/RMT

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The Reliability Modeling Toolkit (RMT)

The Reliability Modeling Toolkit (RMT) is an R-based library of educational tools specifically designed to execute computationally involved and challenging reliability modeling and analytical calculations.

Documentation

  • Documentation is included as standard R help files

Key Applications and Functions

  • Probabilitsic physics-of-failure analysis
  • Stress-Life, Strain-Life, Variable Amplitude Loading
  • Fracture mechanics, wear, creep, and corrosion analysis
  • Reliability Modeling: Probability plotting, least squares estimation of probability parameters, maximum likelihood estimation, Bayesian parameter updating
  • Accelerated Life Testing
  • Step-Stress Accelerated Life Testing
  • Accelerated Degradation Testing
  • Test Driven Development

Getting Started

Installation instructions from source for the RMT:

install.packages("devtools")
library(devtools)
  • The cmdstanr library is required for installation and may not be available on CRAN so it will need to be installed manually first.
install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
  • If Rtools is installed, build from source:
devtools::install_github("Center-for-Risk-and-Reliability/RMT", INSTALL_opts = "--install-tests")
  • Otherwise, use the following:
devtools::install_github("Center-for-Risk-and-Reliability/RMT", build = FALSE, INSTALL_opts = "--install-tests")

Running Unit tests for RMT:

install.packages("testthat")
library(testthat)
library(reliabilityRMT)
test_package("reliabilityRMT")

Source Repository

The Reliability Modeling Toolkit's (RMT) source code repository is hosted here on GitHub.

Licensing

The Reliability Modeling Toolkit (RMT) is licensed under GPLv3.

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The Reliability Modeling Toolkit (RMT) is an R-based library of educational tools specifically designed to execute computationally involved and challenging reliability modeling and analytical calculations.

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