Welcome to ReliaShiny! ReliaShiny is an interactive web application for reliability analysis. The app is built using the shiny package in R. ReliaShiny provides an easy-to-use interface for performing reliability analysis using the WeibullR, WeibullR.ALT, and ReliaGrowR packages in R.
To install ReliaShiny in R:
install.packages("ReliaShiny")
To install the development version:
# devtools::install_github("paulgovan/ReliaShiny")
install.packages("ReliaShiny", repos = c('https://paulgovan.r-universe.dev', 'https://cloud.r-project.org'))
To launch the app:
ReliaShiny::ReliaShiny()
Or to access the app through a browser, visit govan.shinyapps.io/reliashiny/.
Fit Weibull and Lognormal distributions to time-to-failure data using Maximum Likelihood Estimation or Rank Regression. Generate probability plots and contour plots to assess fit and parameter uncertainty.
Model reliability growth using Crow-AMSAA, Piecewise NHPP, or automatic change-point detection. Visualize results with Reliability Growth and Duane plots.
Analyze repairable systems with Power Law, Log-Linear, or Piecewise NHPP models. Visualize cumulative events, event rates, and the Mean Cumulative Function (MCF).
Fit Weibull or Lognormal distributions under accelerated stress conditions using Arrhenius or Power Law life-stress relationships. Visualize ALT probability plots and life-stress relationships.
If you use ReliaShiny in your research, please cite the following:
Govan, P. (2026). ReliaShiny: A Shiny Application for Reliability Analysis. IEEE Reliability Magazine, 1–9. https://doi.org/10.1109/MRL.2026.3669057
Govan, P. (2023). ReliaShiny: A Shiny App Reliability Analysis. R package version 0.2.0. https://doi.org/10.32614/CRAN.package.ReliaShiny
Please note that the ReliaShiny project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.