Solder ball height and substrate coplanarity inspection is essential to the detection of potential connectivity issues in semi-conductor units. Current ball height and substrate coplanarity inspection tools such as laser profiling, fringe projection, and confocal microscopy are expensive, require complicated setup and are slow, which makes them difficult to use in a real-time manufacturing setting. Therefore, a reliable, in-line ball height and substrate coplanarity measurement method is needed for inspecting units undergoing assembly.

The nine The ten papers in this special issue focus on three areas: equipment automation, operations automation, and modeling.

Non-wet solder joints in processor sockets are causing mother board failures. These board failures can escape to customers resulting in returns and dissatisfaction. The current process to identify these non-wets is to use a 2D or advanced X-ray tool with multidimension capability to image solder joints in processor sockets. The images are then examined by an operator who determines if each individual joint is good or bad. There can be an average of 150 images for an operator to examine for each socket. Each image contains more than 30 joints. These factors make the inspection process time consuming and the output variable depending on the skill and alertness of the operator. This paper presents an automatic defect identification and classification system for the detection of non-wet solder joints. The main components of the proposed system 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 in the considered images with high accuracy without the need for training data or reference images. An automatic mapping procedure which maps the positions of all joints to a known Master Ball Grid Array file is used to get the precise label and location of the suspect joint for display to the operator and collection of non-wet statistics. The accuracy of the proposed system was determined to be 95.8% based on the examination of 56 sockets (76 496 joints). The false alarm rate is 1.1%. In comparison, the detection rate of a currently available advanced X-ray tool with multidimension capability is in the range of 43% to 75%. The proposed method reduces the operator effort to examine individual images by 89.6% (from looking at 154 images to 16 images) by presenting only images with suspect joints for inspection. When non-wet joints are missed, the presented system has been shown to identify the neighboring joints. This fact provides the operator with the capability to make 100% detection of all non-wets when utilizing a user interface that highlights the suspect joint area. The system works with a 2D X-ray imaging device, which saves cost over more expensive advanced X-ray tools with multidimension capability. The proposed scheme is relatively inexpensive to implement, easy to set up and can work with a variety of 2D X-ray tools.

Voids in solder balls can cause board failures. The detection and assessment of voids in solder balls can help in reducing board yield issues caused by incorrect scrapping and rework. X-ray imaging machines make voids visible to the operator for manual inspection. Some existing x-ray inspection systems have void detection algorithms that require the use of intensive manual tuning operations that are time consuming, and inaccurate due to the inability to examine balls overshadowed with other components. In this paper, a robust automatic void detection algorithm is proposed. The proposed method is able to detect voids with different sizes inside the solder balls, including the ones that are overshadowed by board components and under different brightness conditions. Results show that the proposed method achieves a correlation squared in the range of 91% to 97% with ground truth data from a 3D x-ray scan. The proposed algorithm is fully automated and benefits the manufacturing process by reducing operator effort and by providing a cost effective solution to improve output quality.

A massively redundant, tentacle-based robot manipulator is proposed as an alternative to dextrous manipulation by an arm/hand combination. The tentacle is advantageous because it is an all-in-one arm and gripping device capable of a wide variety of configurations and grasps, while maintaining the mechanics of serial manipulators. A method for evaluating the forces and velocities imparted to an arbitrary object by a robot hand is reviewed and extended to include the case where several serial manipulators each come in contact with an object at multiple joints. From this analysis, a quantitative evaluation of grasp manipulability and stability is developed that accounts for multiple object contacts for each serial manipulator in the system. A method of applying both precision and power grasps to three-dimensional objects using a tentacle is presented that allows for easy transition between the two by merely curling or uncurling links from around the object. This method helps reduce the number of complexity of grasp configurations. Numerical simulations of different tentacle manipulators and grasps are given.>