A case study for improving the quality of a wave-soldering process that produced printed circuit boards (PCB's) is presented. A mixed-level fractional factorial design was implemented in a high-volume production system during normal operational hours. The observed ordered-categorical data from the bottom-side soldered leads were weighted to formulate the average, spatial uniformity, and dispersion process performance measurements. For lead classes like the integrated circuit and printed grid array, a polynomial model was established using the least squares method with weights provided by a dispersion function. The main-effect and interaction model terms were selected by forward and all-subsets regressions. Production quotas, topside defects, presoldering board temperature, and variance models were used to set the constraints for simultaneously optimizing predictions from the average and the uniformity models of all leads. A nonlinear optimization routine was used to determine the best and most robust settings for the continuous and discrete process variables. Results from a confirmatory experiment showed an improvement of mean soldering quality by 33% and of uniformity by 39%.
A case study of improving the quality of a complex wave soldering process which produces printed circuit boards (PCB) is presented in this article. Experimental design with a mixed-level fractional factorial structure was implemented in a high-volume production system during regular hours of operation. The observed ordered-categorical data from the bottom-side joints of PCB's are weighted to formulate performance measurements such as the average and the uniformity of solder-qualities. These summary statistics take into account the spatial correlation that occurs in joint-quality within the same type of components such as integrated circuit and PGA's. Several polynomial regreSSIOn models with possible higher-order interactions between controllable variables are fitted to these statistics. Dispersions effects are computed and modeled from repetitions of the average and the uniformity measurements. Topside soldering quality, pre-soldering board temperature and dispersion effects are used to set the constraints for optimizing the average and the uniformity soldering-quality simultaneously. A nonlinear programming method of constrained optimization is employed to determine the best and most robust settings for the continuous and discrete process variables. The analysis of results from a small confirmatory experiment shows a completely uniform soldering-quality and an improvement of 32.85% in mean scores in comparing samples of 20 PCB's taken before and after optimization.
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