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Ensuring First Article Inspection Accuracy for High-Density PCBs

2026-01-19 125

With the continuous development of electronic products towards miniaturization and high density, the number of components on PCBs is increasing, and the spacing between components is getting smaller and smaller. Traditional manual FAI relies on the experience and sense of responsibility of operators, and it is easy to have misjudgments and omissions due to visual fatigue when facing high-density PCBs with 01005 package components and BGA/QFN special-shaped components. At the same time, the judgment standards of different operators are inconsistent, resulting in poor consistency of inspection results, which may lead to unqualified products flowing into the market and affecting brand reputation.
The fully automated flying probe FAI machine effectively solves the problem of low inspection accuracy with high-precision hardware configuration and intelligent detection technology. Equipped with a high-precision visual positioning system and micron-level probes, the machine can achieve a detection accuracy of ±0.01mm, which can accurately identify component polarity, pin short circuits/open circuits, and other potential quality issues. The AI visual comparison technology adopted by the machine uses a 12MP dual telecentric lens and ring shadowless light source, which can complete the detection of polarity, silk screen, warping, and missing parts in 0.3 seconds, with a false judgment rate of less than 0.5%.
For high-reliability application fields such as aerospace and medical electronics, the accuracy and consistency of FAI are crucial. The automated flying probe FAI machine can provide stable and reliable inspection results, completely avoiding interference from human factors, and ensuring that each batch of products meets the strict quality standards. This not only helps manufacturers reduce the cost of rework and scrap but also enhances the trust of customers in the products.
Keywords: flying probe FAI accuracy, high-density PCBs, BGA/QFN inspection, AI visual inspection

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