In Auburngrads/SMRD: Statistical Methods For Reliability Data

SMRD:::vinny()
library(SMRD)

In this echapter...

BearingCage.ld <- frame.to.ld(bearingcage,
                              response.column = 1, 
                              censor.column = 2,
                              case.weight.column = 3)

BearingCage.mlest.weib <- mlest(BearingCage.ld,
                                dist = "Weibull")

CondProbInterval2(BearingCage.mlest.weib,
                  age = 50,
                  tL = 50,
                  tU = 350)

CondProbInterval2(BearingCage.mlest.weib,
                  age = 150,
                  tL = 150,
                  tU = 450)

Table 12.1 from Meeker and Escobar (1998)

PredictTable(BearingCage.mlest.weib,
             FtimeStart = 0, 
             FtimeEnd = 300)

CondProbInterval(mu = 3.7393, 
                 sigma = 0.7639,
                 distribution = "lognormal",
                 age = 1,
                 tL = 1,
                 tU = 36)

DeviceN data set

DeviceN.ld <- frame.to.ld(devicen,
                          response.column = "months", 
                          censor.column = "event",
                          case.weight.column = "counts")

DeviceN.mlest.lnorm <- mlest(DeviceN.ld,
                             dist = "Lognormal")

CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 1,
                  tL = 1,
                  tU = 36)
CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 2,
                  tL = 2,
                  tU = 36)
CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 1,
                  tL = 1,
                  tU = 2)
CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 2,
                  tL = 2,
                  tU = 3)

DeviceN.mlest.weib <- mlest(DeviceN.ld,
                            dist = "Weibull")

CondProbInterval2(DeviceN.mlest.weib,
                  age = 1,
                  tL = 1,
                  tU = 36)

CondProbInterval2(DeviceN.mlest.weib,
                  age = 2,
                  tL = 2,
                  tU = 36)

CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 1,
                  tL = 1,
                  tU = 2)

CondProbInterval2(DeviceN.mlest.lnorm,
                  age = 2,
                  tL = 2,
                  tU = 3)

PredictTable(DeviceN.mlest.lnorm,
             FtimeStart = 0,
             FtimeEnd = 1)

PredictTable(DeviceN.mlest.lnorm,
             FtimeStart = 1,
             FtimeEnd = 2)

PredictTable(DeviceN.mlest.lnorm,
             FtimeStart = 0,
             FtimeEnd = 36)

PredictTable(DeviceN.mlest.lnorm,
             FtimeStart = 0,
             FtimeEnd = 36,
             warranty.time = 36)

PredictTable(DeviceN.mlest.weib,
             FtimeStart = 1,
             FtimeEnd = 2)

PredictTable(DeviceN.mlest.weib,
             FtimeStart = 0,
             FtimeEnd = 36)

No warranty enforcement

DeviceN.NoEnforce.lnor <- 
  CumulativePredictTable(DeviceN.mlest.lnorm,
                         time.increment = 1,
                         number.time.units.ahead = 50,
                         warranty.time = 1000)

PlotCumulativePredictTable(DeviceN.NoEnforce.lnor,
                           plot.what = "density")

PlotCumulativePredictTable(DeviceN.NoEnforce.lnor,
                           plot.what="cumulative")

Strict warranty enforcement

DeviceN.Enforce.lnor <-
  CumulativePredictTable(DeviceN.mlest.lnorm,
                         time.increment = 1,
                         number.time.units.ahead = 50,
                         warranty.time = 36)

PlotCumulativePredictTable(DeviceN.Enforce.lnor,
                           plot.what = "density")

PlotCumulativePredictTable(DeviceN.Enforce.lnor,
                           plot.what = "cumulative")

Strict vs. no warranty enforcement (lognormal distribution)

PlotCumulativePredictTable(DeviceN.NoEnforce.lnor,
                           plot.what = "density",
                           ylim = c(0,10000))

PlotCumulativePredictTable(DeviceN.Enforce.lnor,
                           plot.what = "density",
                           add = TRUE,
                           lty = 3,
                           lwd = 3)

PlotCumulativePredictTable(DeviceN.NoEnforce.lnor,
                           plot.what = "cumulative")

PlotCumulativePredictTable(DeviceN.Enforce.lnor,
                           plot.what = "cumulative",
                           add = TRUE,
                           lty = 3,
                           lwd = 3)

No warranty enforcement

DeviceN.NoEnforce.weib <-
  CumulativePredictTable(DeviceN.mlest.weib,
                         time.increment = 1,
                         number.time.units.ahead = 50,
                         warranty.time = 1000)

PlotCumulativePredictTable(DeviceN.NoEnforce.weib,
                           plot.what = "density")

PlotCumulativePredictTable(DeviceN.NoEnforce.weib,
                           plot.what = "cumulative")

Strict warranty enforcement

DeviceN.Enforced.weib <-
  CumulativePredictTable(DeviceN.mlest.weib,
                         time.increment = 1,
                         number.time.units.ahead = 50,
                         warranty.time = 36)

PlotCumulativePredictTable(DeviceN.Enforced.weib,
                           plot.what = "density")

PlotCumulativePredictTable(DeviceN.Enforced.weib,
                           plot.what = "cumulative")

Strict vs. no warranty enforcement (Weibull distribution)

PlotCumulativePredictTable(DeviceN.NoEnforce.weib,
                           plot.what = "density",
                           ylim = c(0,NA))

PlotCumulativePredictTable(DeviceN.Enforced.weib,
                           plot.what = "density",
                           add = TRUE,
                           lty = 3,
                           lwd = 3)

PlotCumulativePredictTable(DeviceN.NoEnforce.weib,
                           plot.what = "cumulative")

PlotCumulativePredictTable(DeviceN.Enforced.weib,
                           plot.what = "cumulative",
                           add = TRUE,
                           lty = 3,
                           lwd = 3)