Multi-Classifier Approaches for Post-Placement Surface-Mount Devices Quality Inspection

In the continuing effort to shrink the electronics components and assemblies, the need for streamlined production processes and quality assurance is emerging stronger than ever. Surface Mounted Devices (SMD) is one of the breakthrough techniques that drove printedcircuit board production to a new level, increasing substantially the component density and reducing the size of produced circuits. Quality inspection of SMD is recognized as a critical and complex task in the production process (Bartlet et al., 1988). Speed is also important as to reduce the overall production costs (Lecklider, 2004). Specific SMD defects have been reported in the literature (Loh & Lu, 1999) including component misplacement and absence, component with wrong polarity, solder joint defects and component shifting. Much of the current research efforts are concentrated on detecting solder joint defects. The types of solder joint defects include surplus solder, insufficient solder and lacking solder. Component shifting has also been reported as a special solder joint defect. Among the methods employed by industrial automatic solder-joint quality inspection systems are laser infrared signatures, digital radiography, laser Doppler vibrometry or laser acoustic microscopy. However, the high cost, low throughput and sampling loss of the above approaches call for research on non-destructive machine vision systems. Several optical inspection systems for solder joints have been reported (Bartlet et al., 1988; Capson & Eng, 1988; T-H. Kim et al., 1999; Ryu & Cho, 1997), using different illumination techniques and defect classification schemes. There have also been efforts to evaluate data fusion to combine data from various sensors for quality inspection of soldering processes (Lacey et al., 1993). In an earlier work (Zervakis et al., 2004), our effort focused on overcoming the degrading effects of illumination and/or inaccurate measurements by exploiting stochastic modeling of lead displacement and its effects. As part of the aforementioned work, we have provided a novel framework to inspect the placement quality of SMD immediately after they have been placed in wet solder paste on a Printed Circuit Board (PCB). This type of inspection has the advantage that the critical data is available immediately after placement, so no extra time and components are spent on an already faulty PCB. Three measures of quality placement from individual lead images are of general interest, namely overlap, insulation distance and slump gap. Under general geometric conditions and using simple geometric relations, it can be shown that these measures are only affected by the displacement (i.e., shift and rotation)