Quantifying Microvia Plating Fatigue and Target Pad Separation Rates under Rapid Thermal Cycling
Continuous high-speed Kelvin monitoring during rapid thermal cycling isolates latent target pad separations that re-nest and pass static ambient tests.
Weibull Analysis
Distribution Modeling
Statistical reliability modeling based on extreme value distribution functions calculates cumulative failure probabilities and lifespan characteristics for electronic components and solder joints. Applying Weibull analysis to thermal cycling or mechanical vibration test data allows reliability engineers to characterize failure rates without assuming a normal or exponential distribution. The resulting two-parameter or three-parameter mathematical model determines the characteristic life and shape parameter of a component population under stress testing.
In printed circuit assembly qualification, this method transforms limited laboratory failure samples into actionable lifetime predictions for field deployments.
Wearout Identification
The slope of the Weibull plot, known as the shape parameter or beta value, reveals the underlying failure mechanism affecting the assembly population. A shape parameter value less than one indicates infant mortality caused by manufacturing defects, such as solder voids or trace micro-cracks. Values near one signal random failures occurring independently of operational age, whereas values significantly greater than one indicate wearout mechanisms like fatigue cracking in solder joints or microvia insulation breakdown.
Tracking slope changes across different stress acceleration levels helps test engineers separate process defects from inherent material wearout boundaries.
Test Extrapolation
Fitting stress test data to Weibull distribution curves enables accurate prediction of lower percentile failure times, such as the B1 or B10 life of an assembly design. Operating life predictions derived from these statistical plots validate warranty calculations and confirm compliance with contract reliability targets.