SMRP BoK Review Workbook

The beta value is simply a measure of the slope of the probability plot.

Why: The Weibull distribution is so frequently used for reliability analysis
because one set of math (based on the weakest link in the chain will cause
failure) described infant mortality, chance failures, and wear-out failures.

When: Use Weibull analysis when you have age-to-failure data. When you
have age-to-failure data by component, the analysis is very helpful because
the b-values will tell you the modes of failure which no other distribution will
do this!

Where: When in doubt, use the Weibull distribution to analyze age-to-failure
data. It works with test data. It works with field data. It works with warranty
data. It works with accelerated testing data. The Weibull distribution is valid
for ~85-95% of all life data, so play the odds and start with Weibull analysis.

Weibull distributions have been used effectively to help determine both the
pattern of failure that a specific component experiences for a specified failure
mode. In addition to identifying the failure pattern it also provides an accurate
assessment of the characteristic life of the component for the same failure
mode.

When experiencing an infant mortality problem, it does not make sense to do
planned or time-based replacement maintenance, as it will only increase the
chance of failure when the component comes back on-line.

Life Cycle Costing Benchmarks

Design & Development

▪ 10 – 20% - defense

▪ 5 – 10% - industrial

Production / Fabrication / Installation

▪ 20 – 30% - defense

▪ 10 – 20% - industrial

Operation & maintenance

▪ 50 – 70% - defense

▪ 65 – 85% - industrial

Disposal

▪ < 5% - defense

▪ < 5% - industrial