Autors: Petkov N., Ivanova, M. S.
Title: Printed circuit board and printed circuit board assembly methods for testing and visual inspection: a review
Keywords: Artificial intelligence, Automation, Machine learning, Printed circuit board assemblie testing, Printed circuit board testing, Visual inspection

Abstract: Testing and visual inspection of printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) are important procedures in the manufacturing process of electronic modules and devices related to locating and identifying possible defects and failures. Earlier defects detection leads to decreasing expenses, time and used resources to produce high quality electronics. In this paper an exploration and analysis about the current research regarding methods for PCB and PCBA testing, techniques for defects detection and vusial inspection is performed. The impact of machine and deep learning for testing and visual inspection procedures is also investigated. The used methodology comprises bibliometric approach and content analysis of papers, indexed in scientific database Scopus, considering the queries: “PCB and testing” and “PCB and testing”, “printed circuit board assembly and testing” and “PCBA and testing”, “PCB defect detection” and “PCBA defect detection”, “PCB and visual inspection”, and “PCBA and visual inspection”. The findings are presented in the form of a framework, which summarizes the contemporary landscape of methods for PCBs and PCBAs testing and visual inspection.

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Issue

Bulletin of Electrical Engineering and Informatics, vol. 13, pp. 2566-2585, 2024, Indonesia, https://doi.org/10.11591/eei.v13i4.7601

Copyright IAES

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