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Optimizing BGAs and QFNs Using Physics of Failure

Posted by Craig Hillman on Oct 7, 2016 10:40:00 AM

Optimizing-BGAs-QFNs.jpgIn our recent BGA and QFN Failure Mitigation blog, we explored the popularity of BGA and QFN packages in today’s technologies, and the challenges they present – specifically a greater risk of solder joint failure.

“Band aid” fixes of underfilling, edge bonds and corner staking are available to remedy BGA failure; however, none are the complete solution offered by physically changing the package design using Physics of Failure (PoF) and Sherlock Automated Design Analysis™ software.

Predicting Solder Joint Lifetime

During thermal cycle testing, the differing expansion/contraction behaviors of the solder and the materials to which it is attached cause stress, and the strain deforms the solder. The extent of the strain dictates the lifetime of the solder joint – the higher the strain, the more the solder joint is damaged and the shorter the lifetime.

By contrast, Sherlock Automated Design Analysis™ software uses physics-based degradation algorithms to predict vibration and mechanical shock performance over a range of temperatures, not just the standard 25°C for electronics. The virtual tool also develops predictive models and design rules based critical drivers like:

  • Component and board Coefficient of Thermal Expansion (CTE) and elastic modulus (compliance)
  • Volume and thickness of solder
  • Length of component
  • Solder fatigue properties

Based on these critical drivers and physics-based degradation algorithms, stress and strain calculations can be made and strain energy dissipation can be determined.

Sherlock bases its time to failure predictions on strain energy and allows engineers to make design adjustments on-screen, before layout – saving time and money while extending time to failure and meeting reliability goals.

Developing a PoF Process

Using Physics of Failure to its best advantage means developing and following a three-step process:

Step 1: Implement PoF in component engineering or parts selection

  • Assess risk of solder joint failure for, and physically inspect, each new component considered for addition to the approved vendor list 

Step 2: Benchmark PoF prediction

  • Run a PoF simulation and compare to the supplier’s test environment
  • Lacking test data, identify reliability by similarity (RBS) equivalent and choose to either test or move forward with PoF only
  • Once the component passes PoF in RBS, test it with your particular package

Step 3: Perform PoF before layout

  • Running PoF after layout is moot. It’s too late to make design changes to components – stackups, bond pad sizing, stencil thickness, placement, attachments, etc.

Systematic processes simplify and improve reliability prediction. Sherlock uses data input, analysis, reporting, and recommendations to translate ECAD and MCAE data into 3D finite element models, automate thermal derating and democratize the thermal and mechanical analysis of electronics. BGAs and QFNs can be optimized in hours, not weeks.

Learn more about solving reliability issues with PoF and Sherlock in Selecting the Right Mitigation for BGAs and QFNs. Click the button below to download your free copy of this informative webinar.
Select the Right Mitigation for BGAs and QFNs webinar

Topics: Design for Reliability

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