{"id":31710399,"url":"https://github.com/paulgovan/relialearnr","last_synced_at":"2026-03-09T18:37:13.315Z","repository":{"id":168329247,"uuid":"644030886","full_name":"paulgovan/ReliaLearnR","owner":"paulgovan","description":"Learning Modules for Reliability Analysis","archived":false,"fork":false,"pushed_at":"2025-10-06T01:29:56.000Z","size":11979,"stargazers_count":0,"open_issues_count":6,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-06T03:22:07.959Z","etag":null,"topics":["life-data-analysis","r","reliability","tutorial","weibull-analysis"],"latest_commit_sha":null,"homepage":"https://paulgovan.github.io/ReliaLearnR/","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/paulgovan.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE.md","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":"codemeta.json","zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2023-05-22T17:00:09.000Z","updated_at":"2025-10-06T01:25:55.000Z","dependencies_parsed_at":"2024-07-25T01:43:49.492Z","dependency_job_id":"ec729de1-c26e-4be8-b04e-74c60dee0686","html_url":"https://github.com/paulgovan/ReliaLearnR","commit_stats":{"total_commits":42,"total_committers":1,"mean_commits":42.0,"dds":0.0,"last_synced_commit":"e8d98270ce0ce3c63f0ae22dcfdd5831d57612d3"},"previous_names":["paulgovan/weibullr.learnr","paulgovan/relialearnr"],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/paulgovan/ReliaLearnR","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulgovan%2FReliaLearnR","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulgovan%2FReliaLearnR/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulgovan%2FReliaLearnR/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulgovan%2FReliaLearnR/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/paulgovan","download_url":"https://codeload.github.com/paulgovan/ReliaLearnR/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulgovan%2FReliaLearnR/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279000720,"owners_count":26082879,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-08T02:00:06.501Z","response_time":56,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["life-data-analysis","r","reliability","tutorial","weibull-analysis"],"created_at":"2025-10-09T00:27:15.789Z","updated_at":"2026-03-09T18:37:13.300Z","avatar_url":"https://github.com/paulgovan.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# ReliaLearnR \u003ca href=\"https://paulgovan.github.io/ReliaLearnR/\"\u003e\u003cimg src=\"man/figures/logo.png\" align=\"right\" height=\"136\" alt=\"ReliaLearnR website\" /\u003e\u003c/a\u003e\n\n\u003c!-- badges: start --\u003e\n[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![CRAN\nstatus](https://www.r-pkg.org/badges/version/ReliaLearnR)](https://CRAN.R-project.org/package=ReliaLearnR)\n[![R-CMD-check](https://github.com/paulgovan/ReliaLearnR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/paulgovan/ReliaLearnR/actions/workflows/R-CMD-check.yaml)\n[![Codecov test coverage](https://codecov.io/gh/paulgovan/ReliaLearnR/graph/badge.svg)](https://app.codecov.io/gh/paulgovan/ReliaLearnR)\n[![](http://cranlogs.r-pkg.org/badges/last-month/ReliaLearnR)](https://cran.r-project.org/package=ReliaLearnR)\n[![](http://cranlogs.r-pkg.org/badges/grand-total/ReliaLearnR)](https://cran.r-project.org/package=ReliaLearnR)\n[![DOI](https://jose.theoj.org/papers/10.21105/jose.00302/status.svg)](https://doi.org/10.21105/jose.00302)\n\u003c!-- badges: end --\u003e\n\nWelcome to **ReliaLearnR!** This package provides interactive learning modules on\nfundamental concepts in reliability analysis. The modules are built\nusing the `learnr` package and cover topics such as life data analysis,\nreliability testing, and reliability, availability, and maintainability\n(RAM) concepts. The package also includes helper functions for common\nRAM calculations. \n\n## Installation\n\nTo install ReliaLearnR in R:\n\n``` r\ninstall.packages('ReliaLearnR')\n```\n\nTo install the development version:\n\n``` r\n# install.packages(\"pak\")\npak::pak(\"paulgovan/ReliaLearnR\")\n```\n\nNote: You may be prompted to update dependent packages before installing. To do so,\ntype 1 (All) when prompted.\n\n## Recommended Background\n\nReliaLearnR is designed for students and professionals who are interested\nin learning the fundamentals of reliability analysis. No prior experience is \nrequired, but a basic understanding of R and statistics is helpful. For a complete beginners' \nguide to R, check out the resources at\n[https://education.rstudio.com/learn/beginner/](https://education.rstudio.com/learn/beginner/).\n\n## Usage\n\nThe package includes three interactive learning modules. To launch the modules, \nload the package and call the respective function:\n\n-   `ram()` - A quick reference for common Reliability,\n    Availability, and Maintainability (RAM) concepts \n-   `lda()` - An introduction to Life Data\n    Analysis\n-   `rt()`- An introduction to Reliability Testing\n\nThe modules can also be accessed in a browser at\n[paulgovan.shinyapps.io/RAMAnalysis/](https://paulgovan.shinyapps.io/RAMAnalysis/),\n[paulgovan.shinyapps.io/LifeDataAnalysis/](https://paulgovan.shinyapps.io/LifeDataAnalysis/) and\n[paulgovan.shinyapps.io/ReliabilityTesting/](https://paulgovan.shinyapps.io/ReliabilityTesting/).\n\n![](https://github.com/paulgovan/ReliaLearnR/blob/master/inst/paper/ReliaLearnR.png?raw=true)\u003c!-- --\u003e\n\nThe package also includes several helper functions for common RAM calculations. These\nfunctions can be used independently of the learning modules:\n\n-   `rel()` - reliability function\n-   `avail()` - availability function\n-   `mttf()` - mean time to failure\n-   `mtbf()` - mean time between failure\n-   `fr()` - failure rate\n\n## Design\n\nThe learning modules are designed to be interactive and engaging, with a\nfocus on practical applications. Each module includes a mix of instructional content, \ncode examples, and exercises to reinforce learning. The modules are self-paced,\nallowing learners to progress at their own speed. \n\nThe original learning modules were provided in a series of workshops, where each \nworkshop covered a specific module over a 1-2 hour period. These workshops were \ndesigned to be completed in a classroom setting with an instructor. The current version \nof the modules has been adapted for self-paced learning, but they can still be used \nin a classroom setting with an instructor. \n\nTo adopt the modules for classroom use, instructors can either access them \nvia the project website or install the package and use the functions directly. \nInstructors can also modify the modules to fit their specific needs, as the source code is \navailable on the project repository. \n\n## Motivation\n\nThis project began as an effort to build upon a reliability program developed at \na major technology company. The original program proved to provide a strong foundation, \nproviding a structured learning opportunity that helped many early-career professionals \nunderstand and apply the fundamental concepts of reliability engineering.\nOver time, however, the proprietary nature of the program limited accessibility \nand adaptability. \n\nRecognizing the importance of keeping reliability learning both relevant and accessible, \nthis project was initiated to create an open-source framework for teaching reliability \nanalysis. By leveraging this framework, this project aims to reach a broader audience, \nencourage collaboration, and ensure that learning resources can evolve as needs and \npriorities change.\n\n## Code of Conduct\n\nPlease note that the ReliaLearnR project is released with a\n[Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). \nBy contributing to this project, you agree to abide by its terms.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaulgovan%2Frelialearnr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpaulgovan%2Frelialearnr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaulgovan%2Frelialearnr/lists"}