The automated optical inspection (AOI) has replaced the manual optical inspection of printed circuit boards (PCBs) in nearly all manufacturing lines. Programming the inspection machines is time consuming and requires a good understanding of the optical inspection domain and printed circuit boards. The process of creating such inspection programs needs to be simplified to enable the user to get to inspection results easier and faster. Over the last few years better and affordable computational hardware helped developing the field of artificial neural networks, called deep learning, to an extent, that it surpassed other state of the art approaches and is used in many optical classification tasks since then. With the ongoing trend of Industry 4.0 AOI systems started not only producing but also storing vast amounts of data. This has the potential to aid the improvement of the inspection machines. This paper will discuss key aspects of AOI as well as basics of deep learning and proposes a new way to integrate these techniques for the manufacturers and users of AOI machines. Additionally, the process of programming AOI inspections will be faster.
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Richter et al. (2017) studied this question.