ttt: Total Time on Test for Repairable Systems

View source: R/ttt.R

tttR Documentation

Total Time on Test for Repairable Systems

Description

ttt calculates the scaled total time on test (TTT) as described in Tests for trend in more than one repairable system and Analysis of Time Between Failures for Repairable Components

As indicated in Analysis of Time Between Failures for Repairable Components this can be used to create a TTT plot.

A TTT plot that follows the line y = x indicates a Homogeneous Poisson Process (HPP) (constant failure rate), while a concave TTT plot indicates a Nonhomogeneous Poisson Process (NHPP). Concave up indicates decreasing failure rate, while concave down indicates increasing failure rate. See: Minitab TTT Plot

Usage

ttt(t, T, fail.trunc = FALSE)

Arguments

t

A list of failure time vectors. Each vector should indicate a different system, i.e. if you have multiple systems each systems' failure times should be in it's own vector.

T

A list of Total Time on Test (TTT) (i.e. test duration) vectors. The vectors in the list should be of length 1, and each vector should indicate a different system, i.e. if you have multiple systems each systems' TTT should be in it's own vector.

fail.trunc

Logical indicating if the test was failure terminated.

Value

The output will be a data.frame with the sorted supplied time values (t), the total time on test (ttt), and the scaled total time on test (scaled_ttt). A plot of scaled_ttt vs ttt would be a TTT plot.

See Also

power_law_process, power_law_mcf, mcf, trend_test, common_beta

Examples

data(amsaa)

# Three systems all time truncated at 200 hours
ttt_df <- ttt(
  t = split(amsaa$Time, amsaa$System),
  T = list(200,200,200),
  fail.trunc = FALSE)

theme_set(theme_bw())
ggplot(ttt_df, aes(x = ttt, y = scaled_ttt)) +
  geom_line(colour = "red") + geom_point() +
  geom_abline(intercept = 0, slope = 1) +
  labs(
    x = "Total Time on Test",
    y = "Scaled Total Time on Test")

 rm(list = c("amsaa", "ttt_df"))


jjw3952/mcotear documentation built on Sept. 2, 2023, 10:30 a.m.