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ReliaLearnR 0.5

New Features

• New rbd() tutorial covering Reliability Block Diagrams and system reliability, including series, parallel, mixed, and k-out-of-n configurations, system MTTF calculation, and an introduction to Fault Tree Analysis — with 4 code exercises and 12 quiz questions.
• New rs() tutorial covering Repairable Systems Analysis, including Non-Homogeneous Poisson Process (NHPP) modeling, Mean Cumulative Function (MCF) estimation, and failure prediction.
• Added a companion book to supplement the interactive tutorials.

Improvements

• All tutorials deepened with more exercises and quiz questions:
  • RAM: Added an interactive failure rate (λ) slider, a Weibull bridge section, and 3 new exercises on series/parallel system reliability.
  • LDA: Added an Anderson-Darling goodness-of-fit section with 2 quiz questions and a model comparison exercise; 2 additional code exercises.
  • RS: Added 3 code exercises covering NHPP fitting, MCF plotting, and failure prediction.
  • RT: Added 3 code exercises covering Duane plotting, RGA, and the Arrhenius acceleration factor.
• NHPP tutorial updated to a MCF-first workflow for a more intuitive learning progression.
• Added DiagrammeR-based visual diagrams to the RBD tutorial.

ReliaLearnR 0.3 (Formerly WeibullR.learnr)

Breaking Changes

• The package has been renamed from WeibullR.learnr to ReliaLearnR to better reflect its broader focus on reliability engineering topics beyond just Weibull analysis.
• All functions and tutorials have been updated to use the new package name ReliaLearnR.
• The WeibullR.learnr() function has been renamed to lda() to simplify its usage.
• The TestR.learnr() function has been renamed to rt() to simplify its usage.
• The RAMR.learnr() function has been renamed to ram() to simplify its usage.
• All references to WeibullR.learnr in documentation and vignettes have been updated to ReliaLearnR.

Other Improvements

• Better (and more) examples and exercises in all tutorials. Improved comments and explanations. https://github.com/paulgovan/ReliaLearnR/issues/21, https://github.com/paulgovan/ReliaLearnR/issues/22, https://github.com/paulgovan/ReliaLearnR/issues/23, https://github.com/paulgovan/ReliaLearnR/issues/25, https://github.com/paulgovan/ReliaLearnR/issues/41.
• New RAM vignette https://github.com/paulgovan/ReliaLearnR/issues/32.

Minor Improvements and bug fixes

• Improved package documentation https://github.com/paulgovan/ReliaLearnR/issues/20, https://github.com/paulgovan/ReliaLearnR/issues/24, https://github.com/paulgovan/ReliaLearnR/issues/26, https://github.com/paulgovan/ReliaLearnR/issues/34, https://github.com/paulgovan/ReliaLearnR/issues/35, https://github.com/paulgovan/ReliaLearnR/issues/50, https://github.com/paulgovan/ReliaLearnR/issues/51, https://github.com/paulgovan/ReliaLearnR/issues/52, https://github.com/paulgovan/ReliaLearnR/issues/50.
• Minor Improvements and bug fixes https://github.com/paulgovan/ReliaLearnR/issues/27

WeibullR.learnr 0.2

• Now with a new Reliability Testing tutorial called TestR.learnr() that covers Reliability Growth Analysis (RGA) and Accelerated Life Testing (ALT)
• Other minor improvements and bug fixes https://github.com/paulgovan/ReliaLearnR/issues/37.

WeibullR.learnr 0.1.3

Minor Improvements and bug fixes

• Update contact info
• Update citation

WeibullR.learnr 0.1.2

Initial release

• Weibullr.learnr function

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.