Ph.D. Proposal Presentation by Jennifer Muncy
Wednesday, January 29, 2003
(Dr. Daniel Baldwin, advisor)
"Predictive Failure Model of Flip Chip on Board Component Level Assemblies"
Environmental stress tests, or accelerated life tests, apply stresses to electronic packages that exceed the stress levels experienced in the field. In theory, these elevated stress levels are used to generate the same failure mechanisms that are seen in the field, only at an accelerated rate. The methods of assessing reliability of electronic packages can be classified into two categories: a statistical failure based approach and a physics of failure based approach. This research uses a statistical based methodology to identify the critical factors in reliability performance of a flip chip on board component level assembly and a physics of failure based approach to develop a low cycle strain based fatigue equation for flip chip component level assemblies. The critical factors in determining reliability performance were established via experimental investigation as well as finite element analysis. This methodology differs from other strain based fatigue approaches because it is not an empirical fit to experimental data; it incorporates regression analysis results into the constants for the strain based fatigue equation. The end product is a general flip chip on board equation rather than one that is specific to a certain test vehicle or material set, also incorporating the effect of process defects into the equation. Approximately 3000 test vehicles have been subjected to a battery of testing including: air-to-air thermal cycling (AATC), high temp storage, liquid/liquid thermal shock (LLTS), and JEDEC pre-conditioning. These test vehicles incorporate four different test die, eight board configurations, two no-flow underfill materials, and two substrate metalizations. A 3D model of a flip chip on board structure has been generated in ANSYS, and the results of various low cycle strain based fatigue equations [Lau, Hong, Engelmaier] were used as fatigue life predictors along with the results of the proposed strain based fatigue equation, these results were then compared to the experimental results.