|The RELIABILITY Procedure
The RELIABILITY procedure
provides tools for reliability and survival data analysis
and for recurrence data analysis.
You can use this procedure to
- construct probability plots and fitted life distributions
with left-, right-, and interval-censored lifetime data
- fit regression models, including
accelerated life test models, to combinations of left-, right-,
and interval-censored data
- analyze recurrence data from repairable systems
These tools benefit reliability
engineers and industrial statisticians working with product
life data and system repair data.
They also aid workers in other fields, such as
medical research, pharmaceuticals, social sciences, and business, where survival
and recurrence data are analyzed.
Most practical problems
in reliability data analysis involve right-censored or
The RELIABILITY procedure provides probability plots of
uncensored, right-censored, and interval-censored data
when all the failure data have common interval endpoints.
Features of the RELIABILITY procedure include
- probability plotting and parameter estimation for the common
life distributions: Weibull, exponential,
extreme value, normal, lognormal, logistic, and
loglogistic. The data can be complete, right censored, or interval
- maximum likelihood estimates of distribution
parameters, percentiles, and reliability functions
- both asymptotic normal and likelihood ratio confidence intervals
for distribution parameters and percentiles. Asymptotic
normal confidence intervals for the reliability function are also
- estimation of distribution parameters by least squares
fitting to the probability plot
- Weibayes analysis, where there are no failures and where the data
analyst specifies a value for the Weibull shape parameter
- estimates of the resulting distribution when
specified failure modes are eliminated
- plots of the data and the fitted relation
for life versus stress in the analysis of
accelerated life test data
- fitting of regression models to life data, where the
life distribution location parameter is a linear function of
The fitting yields maximum likelihood estimates of
parameters of a regression model with a Weibull, exponential,
extreme value, normal, lognormal, logistic and
loglogistic, or generalized gamma distribution.
The data can be complete, right censored, left censored,
or interval censored.
For example, accelerated life test data can be modeled
with such a regression model.
- nonparametric estimates and plots of the mean cumulative
function for cost
or number of repairs and
associated confidence intervals from repair data from
Some of the features provided in the RELIABILITY procedure
are available in other SAS procedures.
You can construct probability plots of life data
with the CAPABILITY procedure; however, the CAPABILITY procedure is
intended for process capability analysis rather than
reliability analysis, and the data must be complete, that is,
The LIFEREG procedure
fits regression models with life distributions such as the Weibull,
lognormal, and loglogistic to left-, right-, and interval-censored data.
The RELIABILITY procedure
fits the same distributions and regression models as the LIFEREG
procedure and, in addition,
provides a graphical display of life data in probability plots.
Lawless (1982), Nelson (1990), Nelson (1982), and Tobias and
Trindade (1995) provide
many examples taken from diverse fields and
describe the analyses provided by
the RELIABILITY procedure.
Nelson emphasizes reliability data analysis from an engineering
The features of the procedure that deal with
the analysis of repair data from systems
are based on the work of
Nelson (1995), Nelson (1988),
Doganaksoy and Nelson (1991), and Nelson and Doganaksoy (1989),
who provide examples of repair data analysis.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.