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ReliaGrowR

Introduction

Welcome to ReliaGrowR! This package provides modeling and plotting functions for Reliability Growth Analysis (RGA) and Repairable Systems Modeling, including:

Reliability Growth Analysis

  • Duane Analysis
  • Crow-AMSAA
  • Piecewise NHPP
  • Piecewise NHPP with Change Point Detection

Repairable Systems Modeling

  • Mean Cumulative Function (MCF)
  • Power Law NHPP
  • Log-Linear NHPP

RGA is focused on improving reliability during development and testing of products, while repairable systems modeling tracks recurrence patterns for fielded systems that can be repaired and returned to service. By analyzing failure data, both approaches help engineers and researchers identify trends, estimate reliability parameters, and support decision-making over time.

To learn more about RGA, please view the RGA vignette. For repairable systems modeling, see the RSA vignette.

Installation

To install the release version of ReliaGrowR, use:

install_packages('ReliaGrowR')

You can install the development version of ReliaGrowR like so:

devtools::install_github('paulgovan/ReliaGrowR')

Example

Here is a basic example of Reliability Growth Analysis. First, load the package.

Next, suppose a machine has failed at the following times with the corresponding number of failures.

times <- c(100, 200, 300, 400, 500)
failures <- c(1, 2, 1, 3, 2)

To perform RGA, use the rga function and plot the results. The plot displays the cumulative failures over time along with the fitted reliability growth model.

result <- rga(times, failures)
plot(result, main = "Reliability Growth Analysis", xlab = "Cumulative Time", ylab = "Cumulative Failures")

Code of Conduct

Please note that the ReliaGrowR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.