This study focuses on the implications that the indiscriminate use of empirical shock metrics can have on shock risk assessment of Ball Grid Array (BGA) components in board level tests. Empirical shock metrics discussed are: 1) shock table applied acceleration, 2) top package acceleration and 3) board strain. Computational modeling and fundamental physics considerations were used to prove that the empirical metrics can lead to wrong conclusions about capability of the BGAs and their performance in the field. These empirical metrics can be considered an indirect indicator of solder joint failure, but because there is no universal (setup independent) correlation to solder joint failure, they are not directly transferable. For a metric to be universal it has to have a unique correlation to solder joint damage, i.e. it has to be based on the physics of failure. For the shock failures, such a metric can be solder joint stress or strain. There are two important implications of this study: 1) when indirect metrics are used, the value determined in the system condition should not be directly used as a test condition requirement and 2) BGA capability when measured by indirect metric will vary as a function of board setup. The indirect metrics can still be used, but they must be scaled to account for structural differences among board setups. For that scaling to be valid, it must be rooted in the knowledge of failure physics and the application of physics based metric. The study provides examples on how empirical metrics scaling should be done and discusses the physics behind it.

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