Helper Functions

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

• rel(failures, total_time): Calculates reliability given the number of failures and total time.
• avail(downtime, total_time): Calculates availability given the downtime and total time.
• mttf(downtime, total_time): Estimates the Mean Time To Failure.
• mtbf(failures, total_time): Estimates the Mean Time Between Failures.
• fr(failures, total_time): 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)

0.9954338

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)

0.9826484

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)

10

To estimate the MTTF for 1000 items that ran for 3 years total:

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

57.63158

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)

9000

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

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

0.00015

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)

0.6065307

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:

result <- qexp(0.1, 0.1)
cat(result)

1.053605