SMTA International Conference Proceedings


Using Weibull Analysis To Interpret Failure Data In Electronics Assembly Stress Testing

Authors: Ronald C. Lasky, Ph.D., P.E.
Company: Indium Corporation
Date Published: 10/13/2013   Conference: SMTA International


Abstract: The Weibull distribution is arguably the most important distribution in failure analysis of leaded and lead-free solder joints. It is the first thought of someone trying to model thermal cycle, drop shock, or other failure modes associated with through-hole and SMT assembly.

The Weibull distribution was invented by Waloddi Weibull in 1931. This invention fact was recounted by Dr. Robert Abernethy in his famous and most useful textbook on Weibull analysis, The New Weibull Handbook.1 This statement may not seem unusual, until we ponder that all common distributions in statistics were discovered, not invented. The three most common statistical distributions are the Normal, Poisson, and Binomial distributions. As an example of a discovered statistical distribution, let’s consider the Binomial distribution. This distribution describes, among other things, the odds of flipping a coin. If one flips a fair coin 60 times, they are most likely to obtain 30 heads (H) and 30 tails (T), but getting 29 H and 31 T, or 32 H and 28 T would not be all that uncommon. Mathematical analysis shows the curve in the results in Figure 1. If a coin flipping experiment is performed many times, this curve will faithfully predict the results. The curve is not invented; it is discovered from the deep theoretical underpinnings of the Binomial Distribution.



Members download articles for free:

Not a member yet?

What else do you get when you join SMTA? Read about all of the benefits that go along with membership.

Notice: Sharing of articles is restricted to just your immediate work group. Downloaded papers should not be stored on an external network or shared on the internet.


Back


SMTA Headquarters
6600 City West Parkway, Suite 300
Eden Prairie, MN 55344 USA

Phone +1 952.920.7682
Fax +1 952.926.1819