https://github.com/paulgovan/relialearnr
Learning Modules for Reliability Analysis
https://github.com/paulgovan/relialearnr
life-data-analysis r reliability tutorial weibull-analysis
Last synced: 30 days ago
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Learning Modules for Reliability Analysis
- Host: GitHub
- URL: https://github.com/paulgovan/relialearnr
- Owner: paulgovan
- License: apache-2.0
- Created: 2023-05-22T17:00:09.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2025-10-06T01:29:56.000Z (6 months ago)
- Last Synced: 2025-10-06T03:22:07.959Z (6 months ago)
- Topics: life-data-analysis, r, reliability, tutorial, weibull-analysis
- Language: HTML
- Homepage: https://paulgovan.github.io/ReliaLearnR/
- Size: 11.4 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 6
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
- Codemeta: codemeta.json
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# ReliaLearnR 
[](https://www.repostatus.org/#active)
[](https://CRAN.R-project.org/package=ReliaLearnR)
[](https://github.com/paulgovan/ReliaLearnR/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/paulgovan/ReliaLearnR)
[](https://cran.r-project.org/package=ReliaLearnR)
[](https://cran.r-project.org/package=ReliaLearnR)
[](https://doi.org/10.21105/jose.00302)
Welcome to **ReliaLearnR!** This package provides interactive learning modules on
fundamental concepts in reliability analysis. The modules are built
using the `learnr` package and cover topics such as life data analysis,
reliability testing, and reliability, availability, and maintainability
(RAM) concepts. The package also includes helper functions for common
RAM calculations.
## Installation
To install ReliaLearnR in R:
``` r
install.packages('ReliaLearnR')
```
To install the development version:
``` r
# install.packages("pak")
pak::pak("paulgovan/ReliaLearnR")
```
Note: You may be prompted to update dependent packages before installing. To do so,
type 1 (All) when prompted.
## Recommended Background
ReliaLearnR is designed for students and professionals who are interested
in learning the fundamentals of reliability analysis. No prior experience is
required, but a basic understanding of R and statistics is helpful. For a complete beginners'
guide to R, check out the resources at
[https://education.rstudio.com/learn/beginner/](https://education.rstudio.com/learn/beginner/).
## Usage
The package includes three interactive learning modules. To launch the modules,
load the package and call the respective function:
- `ram()` - A quick reference for common Reliability,
Availability, and Maintainability (RAM) concepts
- `lda()` - An introduction to Life Data
Analysis
- `rt()`- An introduction to Reliability Testing
The modules can also be accessed in a browser at
[paulgovan.shinyapps.io/RAMAnalysis/](https://paulgovan.shinyapps.io/RAMAnalysis/),
[paulgovan.shinyapps.io/LifeDataAnalysis/](https://paulgovan.shinyapps.io/LifeDataAnalysis/) and
[paulgovan.shinyapps.io/ReliabilityTesting/](https://paulgovan.shinyapps.io/ReliabilityTesting/).
The package also includes several helper functions for common RAM calculations. These
functions can be used independently of the learning modules:
- `rel()` - reliability function
- `avail()` - availability function
- `mttf()` - mean time to failure
- `mtbf()` - mean time between failure
- `fr()` - failure rate
## Design
The learning modules are designed to be interactive and engaging, with a
focus on practical applications. Each module includes a mix of instructional content,
code examples, and exercises to reinforce learning. The modules are self-paced,
allowing learners to progress at their own speed.
The original learning modules were provided in a series of workshops, where each
workshop covered a specific module over a 1-2 hour period. These workshops were
designed to be completed in a classroom setting with an instructor. The current version
of the modules has been adapted for self-paced learning, but they can still be used
in a classroom setting with an instructor.
To adopt the modules for classroom use, instructors can either access them
via the project website or install the package and use the functions directly.
Instructors can also modify the modules to fit their specific needs, as the source code is
available on the project repository.
## Motivation
This project began as an effort to build upon a reliability program developed at
a major technology company. The original program proved to provide a strong foundation,
providing a structured learning opportunity that helped many early-career professionals
understand and apply the fundamental concepts of reliability engineering.
Over time, however, the proprietary nature of the program limited accessibility
and adaptability.
Recognizing the importance of keeping reliability learning both relevant and accessible,
this project was initiated to create an open-source framework for teaching reliability
analysis. By leveraging this framework, this project aims to reach a broader audience,
encourage collaboration, and ensure that learning resources can evolve as needs and
priorities change.
## Code of Conduct
Please note that the ReliaLearnR project is released with a
[Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.