Revealing Hidden Defects in Electronic Components With an AI-Based Inspection Method: A Corrosion Case Study

Corrosion on electronic component terminations during assembly can lead to the failure of electronic devices. The terminations of electronic components are susceptible to corrosion when exposed to moisture and other corrosive agents during and before the assembly process. This corrosion can cause physical damage to the terminations, resulting in poor electrical contact and possible failure of the electronic component. In this letter, we present a case study where an automotive production line utilized Cybord’s AI-based inspection system to detect and prevent contamination in the soldering terminations of electronic components. The system interfaced with the vision system of pick-and-place machines in real time and collected bottom-side images of all components placed on printed circuit boards (PCBs). The AI algorithm, based on a 3 billion component database, detected evidence of corrosion, mold, and other contaminants on each component and allowed the removal of poor-quality components from production. The reel was disqualified and sent to a lab for scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) analysis, which confirmed the findings of the AI algorithm that the issue was evidence of oxidation contamination. The results of this case study demonstrate the effectiveness of using AI-based inspection in detecting and preventing contamination in electronic assembly, boosting the overall quality and reliability of the final product.