Solder Joint Inspection on Printed Circuit Boards: A Survey and a Dataset
Furkan Ülger, Seniha Esen Yüksel, Atila Yılmaz, Dinçer Gökcen
Abstract
Surface Mount Technology (SMT) is a procedure for mounting electronic components to the surface of the printed circuit boards (PCB). Although the SMT procedure is more reliable than the conventional through-hole mounting, many errors may occur in SMT lines. In this paper, we surveyed methods presented for the optical inspection of solder joints on PCBs. The methods are grouped by problem-solving approach: reference-based, machine learning/computer vision, deep learning, and 3D reconstruction. We compare and discuss these approaches according to their advantages and disadvantages, with a focus on the more recent deep learning and 3D reconstruction techniques, and list the public datasets for solder joints inspection. Since defective samples rarely occur in the SMT manufacturing lines, public datasets have few defective samples that are essential for the inspection task. To fill this gap, we publish a public dataset with both normal and different types of SMT errors. Our dataset can be used as a benchmark to compare different algorithms. The dataset is available at https://github.com/furkanulger/solder-joint-dataset.