Reliability Analysis with R: A Companion Guide

A companion reference guide to the ReliaLearnR interactive tutorials, covering RAM analysis, life data analysis, reliability testing, repairable systems, and reliability block diagrams, with additional chapters on interactive visualization with ReliaPlotR, web-based analysis with ReliaShiny, reproducible reports with Quarto, and AI-assisted analysis with MCP.

Author

Paul Govan

Published

June 8, 2026

Preface

This book is a companion reference guide to the ReliaLearnR interactive learning modules. Where the tutorials offer hands-on practice with immediate feedback and interactive widgets, this book provides readable, searchable, printable chapters that cover the same material in a narrative format, plus two additional chapters on the wider ReliaLearnR ecosystem.

How to Use This Book and the Tutorials Together

The interactive tutorials and this book cover the same core content but serve different purposes:

Feature Interactive Tutorials This Book
Instant code feedback Yes No
Quiz questions Yes Review questions
Interactive sliders Yes Static equivalents
Searchable / printable No Yes
Copy-paste code Limited Full
Ecosystem chapters (ReliaPlotR, ReliaShiny) No Yes

Recommended workflow: Read a chapter here first to understand the concepts and see the code, then open the corresponding tutorial to practice. The chapter order mirrors the tutorial progression.

The ReliaLearnR Ecosystem

ReliaLearnR is one part of a broader suite of R packages for reliability analysis:

Package Role
ReliaLearnR Interactive learning modules
WeibullR Weibull life data analysis
ReliaGrowR Reliability growth and repairable systems
WeibullR.ALT Accelerated life testing
ReliaPlotR Interactive reliability plots
ReliaShiny Web-based reliability analysis app
Quarto Reproducible document and book publishing system

Installation

Install the core packages needed to run the code in this book:

install.packages(c(
  "ReliaLearnR",
  "WeibullR",
  "ReliaGrowR",
  "WeibullR.ALT",
  "DiagrammeR",
  "ReliaPlotR",
  "ReliaShiny",
  "quarto"
))

Chapter Overview

  1. RAM: Foundational reliability, availability, and maintainability metrics.
  2. Reliability Block Diagrams: Series, parallel, mixed, k-out-of-n systems, and fault tree analysis.
  3. Life Data Analysis: Weibull distribution, censoring, MRR vs. MLE, and contour plots.
  4. Reliability Growth Analysis: Duane and Crow-AMSAA growth models, test planning, and forecasting.
  5. Accelerated Life Testing: Arrhenius and Power Law acceleration models for compressed test time.
  6. Repairable Systems: Power Law Process, MCF, and fleet-level analysis.
  7. Interactive Plots with ReliaPlotR: Publishable interactive reliability charts.
  8. Web-Based Analysis with ReliaShiny: Point-and-click reliability analysis.
  9. Reproducible Reports with Quarto: Literate programming, parameterized reports, and version-controlled reliability analysis.
  10. AI-Assisted Analysis with MCP: Conversational reliability analysis using Model Context Protocol.

The book also includes an Appendix (helper function reference) and a Glossary (key symbols and formulas).

About the Author

Paul Govan is the author of ReliaLearnR, ReliaGrowR, ReliaPlotR, and ReliaShiny. He can be reached at paul.govan2@gmail.com.