DOAJ Open Access 2024

SolDef_AI: An Open Source PCB Dataset for Mask R-CNN Defect Detection in Soldering Processes of Electronic Components

Gianmauro Fontana Maurizio Calabrese Leonardo Agnusdei Gabriele Papadia Antonio Del Prete

Abstrak

The soldering process for aerospace applications follows stringent requirements and standards to ensure the reliability and safety of electronic connections in aerospace systems. For this reason, the quality control phase plays an important role to guarantee requirements compliance. This process often requires manual control since technicians’ knowledge is fundamental to obtain effective quality check results. In this context, the authors have developed a new open source dataset (SolDef_AI) to implement an innovative methodology for printed circuit board (PCB) defect detection exploiting the Mask R-CNN algorithm. The presented open source dataset aims to overcome the challenges associated with the availability of datasets for model training in this specific research and electronics industrial field. The dataset is open source and available online.

Topik & Kata Kunci

Production capacity. Manufacturing capacity

Penulis (5)

Gianmauro Fontana

Maurizio Calabrese

Leonardo Agnusdei

Gabriele Papadia

Antonio Del Prete

Format Sitasi

APA MLA BibTeX

Fontana, G., Calabrese, M., Agnusdei, L., Papadia, G., Prete, A.D. (2024). SolDef_AI: An Open Source PCB Dataset for Mask R-CNN Defect Detection in Soldering Processes of Electronic Components. https://doi.org/10.3390/jmmp8030117

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Informasi Jurnal

Tahun Terbit: 2024
Sumber Database: DOAJ
DOI: 10.3390/jmmp8030117
Akses: Open Access ✓