Efficient Plant July/August 2020 - 6

column | implementations

Weibull
Makes Data
Useful
Dr. Klaus M. Blache
Univ. of Tennessee Reliability
and Maintainability Center
(RMC)

Among other things, a Weibull analysis
can determine reliability trends by using
a small sample size of data.

W

HAT DOES WEIBULL
mean? It refers to one of
numerous probability
distributions that are used to determine
the amount of time that something can
function. A unique feature of the technique is that it can determine reliability
trends by using a small sample size of
data about failures and time. It's adaptable, relatively simple, and offers visual/
easily understood graphics.
The Weibull distribution was invented by Waloddi Weibull in 1937 and
presented in 1951, with poor acceptance.
Eventually, it got traction, was used by
the U.S. Air Force (1970s), and later by
the automotive industry.
Today Weibull analysis is used in
fields such as engineering sciences,
biology, operations, fabrication, testing,
economics, physics, dentistry, welding, hydrology, insurance, aerospace,
safety, and reliability. Software has made
once-tedious calculations relatively easy.
In simplest terms, performing a
Weibull analysis entails compiling
data that represent your life data, then
determining which distribution best describes your data. Then add confidence
intervals, if desired.
There are several types of plots that

+

GET STARTED IN WEIBULL ANALYSIS

My colleague, Wes Fulton, is offering a free demo download file of SuperSMITH
for Windows, including SuperSMITH Weibull, Visual, and YBath. These software
versions have full functionality and can be used to teach Weibull to students, but
the demo versions randomly change input data so real data cannot be analyzed. To
perform analyses requires a licensed full version. Also available is a free tutorial
booklet. Visit https://rmc.utk.edu/events/ to obtain both.
Interested in more? There is a three-day virtual course (October 13 to 15, 2020)
that provides a complete overview of Weibull analysis, starting with the basics of
performing an analysis and interpreting results. Each attendee will receive the
entire SuperSMITH package and a copy of The New Weibull Handbook (latest
edition). You can find the course at https://rmc.utk.edu/events/.

6

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EP2007implementations.indd 6

can be used to enhance the understanding of your data. A typical Weibull plot
is executed on a log-log format on each
axis. If the resulting plot is a straight line,
then it's aligned with a Weibull distribution (showing time to failure). The
vertical axis generally depicts cumulative
percentage failure and the horizontal
axis shows life or aging data, i.e., cycles
of use, bearing life, airplane landings,
miles, parts produced, operational
uptime. A line slope that is <1 indicates
installation flaws, shipping damage, and
other infant-mortality-related failures. A
straight line also indicates a single failure
mechanism.
A non-straight line is an indication
of multiple failure causes. If the slope
is >1, then it's an indication of wear out
failures. The slope of the Weibull plot
is termed beta (β). If beta is equal to 1,
then it depicts random failure. Weibull
investigations also depict which type of
failure your data represents.
A Weibull Analysis can be used to
perform a variety of functions such as
establish product warranty periods, flag
improper maintenance, identify a poor
production run, find component design
flaws, pinpoint failure causes, develop
maintenance strategies, and predict
when spare parts will be needed. Trends
from the analyzed data can help improve
strategic planning. An analysis can also
help you identify your failure types and
better understand their frequency. EP

Based in Knoxville, Klaus M. Blache
is director of the Reliability &
Maintainability Center at the Univ. of
Tennessee, and a research professor
in the College of Engineering.
Contact him at kblache@utk.edu.

JUL/AUG 2020

7/15/20 2:28 PM


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Efficient Plant July/August 2020

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