This paper demonstrates methods for defect detection in printed circuit boards, highlighting the role of machine learning and design rules.
The paper considers such methods of automated optical control of the technology of automatic verification of printed circuit boards as a method of comparison with a reference, a method of checking design rules and a hybrid approach. It is noted that in addition to these methods, special attention is now being paid to research based on the integration of machine learning methods into the automatic optical inspection (AOI) system. The use of genetic algorithms for optimizing AOI for printed circuit boards is described. The description of the listed methods for solving the problems of detecting defects in printed circuit boards (PCBs) is given.
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Shchukarev et al. (2025) studied this question.
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