Empirical Correlations of SAC Thermal Cycling Test Data

Empirical Correlations of SAC Thermal Cycling Test Data 

The correlation coefficient for the power-law trendline of the data in Fig. 1(a) is = 0.64. Clearly, there is a discrepancy between the data and the basic Coffin-Manson approach. The data is replotted in Fig. 1(b) with the following modifications  

The scaling of characteristic lives for the solder crack area is intended to account for differences in crack propagation times through joints of varied sizes. The resulting parameter—char- 

Alloy Composition and Board Finish Effects. ilie data in Fig. 1(b) is replotted in Fig. 2(a) and 2(b) where, instead of showing component types, results are shown according to alloy composition or board finish. Out of the 27 datasets of interest, five had the nominal solder composition Sn-3.9Ag-0.6Cu (SAC 3906) while all the others had the nominal composition Sn-3.8Ag-0.7Cu (SAC 3807). In Fig. 2(a), the SAC 3906 data points are all below the correlation center line. It might be tempting to conclude that the SAC 3807 alloy leads to a slightly longer life than SAC 3906. However, the SAC 3906 population in the analysis is small (5 data points out of a total of 27), and more data is needed to test the statistical differences between the SAC 3807 and SAC 3906 populations. 

In Fig. 2(b), the same data points are grouped and labeled by board finish immersion Ag, OSP, electroless Ni-Au, or unspecified. For a given group, the data is above or below the centerline and no definite trend is visible on the basis of board finishes. For example, looking at the four Ni-Au and OSP data in the upper left of the plot, the OSP points are above the Ni-Au points. The opposite is observed for the Ni-Au and OSP data points in the lower right region of Fig. 2(b). Over a wide range of cyclic shear strains, no board finish appears to provide consistently better results than the others. 

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