3.3 Weibull Analysis
Weibull analysis is used to test the shape factors and MTTF of various primary failure modes. The rule of thumb for Weibull
results is as follows (6):
• Beta values (shape factors) of less than 1 are very rare and would represent a gross design problem more than anything
else. This would be where an item was continually being replaced almost as soon as it entered service.
• Beta values of between 1.3 and 1.7 indicate one of two possibilities: there are multiple failure modes in the category or
more likely, there is a manageable driver on the defect rate such as maintenance quality of work or operational cleanliness.
• Beta values between 1.7 and 2.2 represent achieving a respectable life but there is scope for improvement in the PM
strategy.
• Beta values greater than 2.5 mean that the PMs are doing their job and there is no operational driver to early failure such
as cleanliness or overload.
These descriptions would not be found in the textbooks but represent our experience in analysing the trends in maintenance
work orders.
The Weibull plots all tend to look the same but the key characteristics are:
• The shape factor
• The x intercept – which is the likely minimum time to failure
The MTTF does not particularly help us since we are taking a lot of data over the period of four year, and hence this tends to
remain between 150 to 220 days for just about all failure modes. We are interested to find out if the failure is being driven by
something we can manage (ie the shape factor), and whether we are going to see a potential failure every day, every week or
every month. Since we are dealing with high frequency failure modes in this section (ie the top 10), their potential to occur will
be at least once a week. A typical plot is shown in Figure 2.