**The basic procedure to prepare the data for Weibull analysis is:** [2]
**1) **The failure voltages are ranked in order from lowest to highest.
**2)** The proportion of the population that will fail is calculated. This can be done by several methods, with "median rank" being the most popular.
**3)** Using regression analysis, a best-fitting straight line is drawn through the points as plotted for Lot A (Figure 3-2) and Lot B (Figure 3-3). The Beta and Alpha parameters were also calculated and are shown in Table 1-1.
Beta is a shape parameter, and since values for both lots are significantly over 1.0, this indicates that there is an increasing failure rate and that they are most likely "wear out" models. Neither lot showed a problem with infant mortality. The Alpha parameter indicated that there is approximately a 3.4 volt difference in the distribution of data between lot A and lot B, again showing that lot B has a more robust characteristic.
It is also important to note that the circuit application, maximum operating voltage level and expected maximum temperature of operation needed to be considered when assessing the overall reliability of the capacitors in each lot.
In conclusion, the Weibull analysis shows its main strength in its versatility. Depending on the parameters’ values, the Weibull distribution can approximate an exponential, normal or skewed distribution. Microsoft Excel, as well as other specialized software packages, can often be used to do the statistical and regression analysis needed to analyze Weibull data.
Resources
1) D. Fink and D. Christiansen ed., Electronics Engineers' Handbook, New York, McGraw-Hill, 1989, pp.28-1 to 28-63.
2) Marshall, Jim, "A Surge Step Stress Test for Tantalum Capacitors", KEMET Tech Topics, KEMET Electronics Corp., 1995. |