Helper Functions
In ReliaLearnR: Learning Modules for Reliability Analysis

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(ReliaLearnR)

The ReliaLearnR package includes several helper functions to calculate common reliability metrics. These functions include:

rel(outageTime, totalTime): Calculates reliability given the outage time and total time.
avail(unavailTime, totalTime): Calculates availability given the unavailable time and total time.
mttf(failures, totalTime): Estimates the Mean Time To Failure.
mtbf(failures, totalTime): Estimates the Mean Time Between Failures.
fr(failures, totalTime): Estimates the failure rate.

This vignette provides examples of how to use these functions.

Examples

To calculate the reliability of an item that ran for 3 years total and was failed for 5 of those days:

result <- rel(5, 3 * 365)
cat(result)

To calculate the availability of an item that ran 3 years total, was failed for 5 days, and had scheduled maintenance for 14 days:

result <- avail(5 + 14, 3 * 365)
cat(result)

The MTTR can be estimated with the base function mean. The MTTR for 5 failures with repair times in days of 5, 10, 15, 8, and 12:

result <- mean(c(5, 10, 15, 8, 12))
cat(result)

To estimate the MTTF for an item that failed 5 times over a 3-year period:

result <- mttf(5, 3 * 365)
cat(result)

To estimate the MTBF for an item that failed 5 times over a total time of 45,000 hours:

result <- mtbf(5, 45000)
cat(result)

To estimate the failure rate for 100 items that ran for 5000 hours and had 75 failures:

result <- fr(75, 100 * 5000)
cat(result)

The Exponential failure probability can be estimated with the base function pexp. To estimate the probability of survival at time 5 for an item with a failure rate of 0.1:

result <- 1 - pexp(5, 0.1)
cat(result)

The $B_n$ life for the Exponential distribution can be estimated with the base function qexp. To estimate the B10 life for an item with a failure rate of 0.1: