Introducing a lead-free solder replacement requires studies to be conducted by electronic assembly manufacturers in order to determine process alteration requirements and suitability of current equipment. This paper presents the results of an investigation of the screen-printing and reflow steps of the surface mount technology (SMT) manufacturing process. Experiments were conducted to investigate these two processes using a tin-silver-copper (95.5Sn3.8Ag0.7Cu) solder and a baseline of standard tin-lead (63Sn37Pb). 10/spl times/10 array micro Ball Grid Arrays (BGAs) mounted on 8-layer FR4 printed wiring boards (PWBs) were used with an organic solderability preservative (OSP) finish for use with lead-free components, and a hot air solder level (HASL) finish for use with tin-lead components. The screen-printing experiment investigated the deposition of the solder paste on the board. The parameters used in the investigation were print speed, squeegee pressure, snap-off distance, separation speed and cleaning interval with the responses being measurements of paste height and volume. Optimum screen-printer settings were determined which give adequate paste volume and height and a good print definition. The reflow experiment investigated the following parameters of the temperature profile; preheat, soak and reflow temperatures, and conveyor speed. The solder joints were examined using cross-section analysis and X-ray techniques in order to determine the presence of defects. The outcome of the investigation is a set of optimum settings for the screen-printer and reflow oven for use with SnAgCu lead-free solder.

Two graphical techniques for analyzing step-stress Arrhenius exponential data are presented and compared to maximum likelihood estimation using simulated data. Analysis shows that the graphical technique using least squares estimation is unbiased. Levene's test for equality of variance also shows that the least squares estimator is as efficient as the maximum likelihood estimator. An analysis of outliers provides further evidence that the graphical technique is a valid alternative to maximum likelihood estimation. Indeed, both the maximum likelihood estimator and the least squares estimator are similarly affected by stress-steps that contain no failures. These results, in conjunction with design of experiment analysis are used to formulate guidelines for conducting step-stress testing. A novel algorithm is also proposed that identifies when to switch to the next higher stress-step in order to avoid too many failures at the lower stress-steps. Finally a worked example is included to illustrate the graphical technique.