Feature: Machine Vision


based anomaly detection, or a conventionally-trained variation model. To achieve maximum speed and performance, a combination of both is oſt en recommended. Another example in front-end production is the measurement


of solder balls on the wafer; see Figure 2. Since they provide connection between chip and circuit board, their precise height and diameter and overall uniformity are vital to ensure the ICs’ fl awless operation and reliability. T ree-dimensional image processing technologies, such as 3D surface inspection, shape- based 3D matching and 3D measurement, can be used here for quality inspection. At the back end of the semiconductor manufacture is the wire


bonding stage, where connecting wires between the semiconductor and its housing or other components in the package are being attached. Bond inspection is a proven quality control process,


Figure 1: Detection of microscopic defects on a wafer


especially when packaging the chip. It involves using the utmost precision to check the position of the wire and the integrity of the bond at a microscopic level; see Figure 3. Machine vision technologies do measurements here, with sub-pixel accuracy. T ey reliably detect the slightest gaps and position deviations, even on complex backgrounds; see Figure 4. MVTec’s machine vision soſt ware, like HALCON and MERLIC,


can be used in both, front- and back-end semiconductor production.


Cutting edge T ere are many other examples of how cutting-edge machine vision technologies are optimising semiconductor manufacturing. And, thinking of the ever-growing possibilities of AI, the number of applications will exponentially rise.


Figure 2: Wafer solder balls under magnifi cation


Figure 3: Bonding connections are accurately detected with machine- vision software


Figure 4: Images from semiconductor production


www.electronicsworld.co.uk July/August 2025 23


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