Folks,
In continuing our discussion on Weibull Analysis, let’s assume we assembled some SMT and through-hole PCBs with lead-free solder paste. On this board are also some bottom-side terminated (BTC) components (often called QFNs), that are also assembled with solder preforms. A stress test is performed to test the BTCs. In such a test, the first fail in Weibull analysis is the most important data point. No matter the results of remainder of the data, these later fails cannot undo the effect of a very early first fail.
To understand this concept, let’s look at the Weibull chart below. In many high reliability applications, there may be a requirement that some small percentage of the components under test have at least some minimum reliability.
Figure 1. Weibull Analysis with an Early Fail.
As an example, let’s say that 1% of the components cannot have less than 500 cycles of life. By looking at Figure 1, we see that 1% have less than 150 cycles of life (see arrow.) This one early outlier dramatically affects the Weibull Analysis.
However, if that outlier was removed, as seen in Figure 2, the data suggest that 1% of the components will have a life of 900 cycles. We can see the dramatic effect the first fail has on this result. Note that the first fail does not affect the “scale” or characteristic life much (2647 vs 2682). Hence, the characteristic life, is not a robust metric to use in a high reliability environment. However, the shape or slope is dramatically affected by the early fail as it changes from 2.22 to 4.23 when the early fail is “censored.”
Figure 2. Weibull analysis with the early fail removed (censored).
Why might an outlier like this exist? Almost certainly there is something unusual about the early fail. It might be something like an oxidized pad preventing good wetting of the solder. Perhaps something like this failure mode might be discovered in root cause failure analysis. However, I am typically opposed to censoring data, even with supportive failure analysis. I think the test should be done over. It is often too easy to talk yourself into accepting inconclusive failure analysis.
What is your opinion?
Cheers,
Dr. Ron
Hi Ron,
Thank you for those explanations and comment about censored data in weibull plot analysis. I think that understanding the typical failure mode we address in the weibull study is important . That’s why we have often to perfom failure analysis . If the failure mode of early case (150 cycles in your example ) is not the same one than all others weibull plot condidred by a targeted accelaration factor in the study it might be interesting to give uop this dat . However it might be important to launch a new study regarding this early failure root cause and maybe find the right mitigation or selection (eg componant tests for batch selections as in automotive field) . This apsect is more related to the first slope of the Bath failure curve ; for the rest of the plot we are really in reliability domain.
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