Issue link: https://iconnect007.uberflip.com/i/831357
June 2017 • SMT Magazine 77 seamlessly rotated 360° around a point of inter- est. The inspection process is very simple, fast and extremely effective. The incorporation of the MAP hardware is very simple and straightforward. The MAP de- vice is positioned inside the FP detector be- tween the carbon fiber cover plate and the scin- tillator. Figure 7 shows an image of a MAP de- vice installed into the CMOS detector used in the following examples. Copper Track Identification The ability to recognize the presence of cop- per tracks is useful for a range of inspection ap- plications. Examples include auto-registration of X-ray images to drawing files, checking for missing components and identification of bro- ken tracks in multilayer boards. This technique is not restricted to surface layers which means that the thickness of buried tracks can also be measured. Such measurements cannot be made using standard profilometry methods. Figure 8 shows an example of automated track identification. Here, the track information is displayed as an overlay to the grayscale im- age. The board has three copper layers and each is identified by a different color in the overlay. This type of visualization gives us the ability to compare to a drawing file in a fast and simple way. In some cases, it is important to know the precise thickness of the Cu tracks. For example, circuits involving power devices can overheat if tracks are not sufficiently thick. In the sec- ond example (Figure 9) the precise thickness of the copper is measured, enabling line profiles through copper tracks to be produced. In addi- tion, a full three-dimensional representation of the copper thickness across the entire board can be generated. Lead Solder Detection With the introduction of restrictions on the use of lead-based solder, knowledge of the sol- der type used in manufacturing process has be- come increasingly important in order to ensure compliance. In this section, we show the poten- tial of the MAP technology as a method for au- tomatically identifying the presence of lead sol- der on a PCB. Figure 10 shows the difference in materials space between an 80/20 lead/tin solder and a 99% tin/copper lead-free solder. Wedges of each solder type were measured on a Dage Diamond machine with a MAP fitted to the CMOS detec- tor, at 160 kV and 3.9 W. The materials curves are clearly separated, showing that a machine learning algorithm could be developed to au- 2D X-RAY INSPECTION WITH MATERIALS AND THICKNESS IDENTIFICATION Figure 7: A MAP device installed inside a FP detector. Figure 8: Example of automated Cu track iden- tification using the energy information provided by the MAP technology. The various thicknesses of copper are shown as overlays on the grayscale 2DX absorption image (right). Left: conventional 2DX absorption image.