Non-wet solder joint detection in processor sockets and BGA assemblies
The existence of non-wet solder joints in PCB sockets can cause boards failures and it's necessary to inspect theses sockets to locate any possible defective joints. 2D or advanced x-ray machines are used to image solder joints in processor sockets and make solder joints visible to be examined by the operator who determines if each individual joint is defective or not. This is a very time consuming process since each processor has an average of 150 images with 30 joints per image. An accurate and efficient non-wet detection method is proposed in this paper. The main components of the proposed method consist of region of interest (ROI) segmentation, feature extraction, reference-free classification, and automatic mapping. The ROI segmentation process is a noise-resilient segmentation method for the joint area. The centroids of the segmented joints (ROIs) are used as feature parameters to detect the suspect joints. The proposed reference-free classification can detect defective joints with high accuracy without the need for training data. An automatic mapping method is used to get the precise label and location of the suspect joint. The accuracy of the proposed method was determined to be 95.8% detection rate with 1.1% false alarm rate based on the examination of 56 sockets (500K joints). In comparison, the detection rates of currently available advanced x-ray tools with multi-dimension capability are in the range of 43% to 75%. The proposed method reduces the operator effort by 90%. The presented system identifies neighboring joints to any missed non-wet joints, which provides an operator with the capability to make 100% detection of all non-wets. The proposed scheme works with a 2D x-ray imaging device, which makes the proposed scheme relatively inexpensive to implement, and is very portable and easy to set up as compared to the available advanced x-ray tools with multi-dimension capability.