reliability {survival}  R Documentation 
Reliability data sets
Description
A set of data for simple reliablility analyses, taken from the book by Meeker and Escobar.
Usage
data(reliability, package="survival")
Details

capacitor
: Data from a factorial experiment on the life of glass capacitors as a function of voltage and operating temperature. There were 8 capacitors at each combination of temperature and voltage. Testing at each combination was terminated after the fourth failure.
temperature
: temperature in degrees celcius 
voltage
: applied voltage 
time
: time to failure 
status
: 1=failed, 0=censored


cracks
: Data on the time until the development of cracks in a set of 167 identical turbine parts. The parts were inspected at 8 selected times.day: time of inspection
fail: number of fans found to have cracks, at this inspection
Data set
genfan
: Time to failure of 70 diesel engine fans.
hours
: hours of service 
status
: 1=failure, 0=censored
Data set
ifluid
: A data frame with two variables describing the time to electrical breakdown of an insulating fluid.
time
: hours to breakdown 
voltage
: test voltage in kV

Data set
imotor
: Breakdown of motor insulation as a function of temperature.temp: temperature of the test
time: time to failure or censoring
status: 0=censored, 1=failed
Data set
turbine
: Each of 432 turbine wheels was inspected once to determine whether a crack had developed in the wheel or not.hours: time of inspection (100s of hours)
inspected: number that were inspected
failed: number that failed
Data set
valveSeat
: Time to replacement of valve seats for 41 diesel engines. More than one seat may be replaced at a particular service, leading to duplicate times in the data set. The final inspection time for each engine will have status=0.id: engine identifier
time: time of the inspection, in days
status: 1=replacement occured, 0= not
References
Meeker and Escobar, Statistical Methods for Reliability Data, 1998.
Examples
survreg(Surv(time, status) ~ temperature + voltage, capacitor)
# Replacement of valve seats. In this case the cumulative hazard is the
# natural target, an estimate of the number of replacements by a given time
# (known as the cumulative mean function = CMF in relability).
# When two valve seats failed at the same inspection, we need to jitter one
# of the times, to avoid a (time1, time2) interval of length 0
ties < which(with(valveSeat, diff(id)==0 & diff(time)==0)) #first of a tie
temp < valveSeat$time
temp[ties] < temp[ties]  .1 # jittered time
vdata < valveSeat
vdata$time1 < ifelse(!duplicated(vdata$id), 0, c(0, temp[length(temp)]))
vdata$time2 < temp
fit2 < survfit(Surv(time1, time2, status) ~1, vdata, id=id)
## Not run:
plot(fit2, cumhaz= TRUE, xscale= 365.25,
xlab="Years in service", ylab = "Expected number of repairs")
## End(Not run)