Technical Library | 2020-07-02 13:29:37.0
Industry standards such as J-STD-005 and JIS Z 3284-1994 call for the use of viscosity measurement(s) as a quality assurance test method for solder paste. Almost all solder paste produced and sold use a viscosity range at a single shear rate as part of the pass-fail criteria for shipment and customer acceptance respectively. As had been reported many times, an estimated 80% of the defects associated with the surface mount technology process involve defects created during the printing process. Viscosity at a single shear rate could predict a fatal flaw in the printability of a solder paste sample. However, false positive single shear rate viscosity readings are not unknown.
Technical Library | 2024-04-29 21:19:42.0
Over the years, computer vision and machine learning disciplines have considerably advanced the field of automated visual inspection for Printed Circuit Board (PCB-AVI) assurance. However, in practice, the capabilities and limitations of these advancements remain unknown because there are few publicly accessible datasets for PCB visual inspection and even fewer that contain images that simulate realistic application scenarios. To address this need, we propose a publicly available dataset, "FICS-PCB"1, to facilitate the development of robust methods for PCB-AVI. The proposed dataset includes challenging cases from three variable aspects: illumination, image scale, and image sensor. This dataset consists of 9,912 images of 31 PCB samples and contains 77,347 annotated components. This paper reviews the existing datasets and methodologies used for PCBAVI, discusses challenges, describes the proposed dataset, and presents baseline performances using feature engineering and deep learning methods for PCB component classification.
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