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.

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

Fontana G.
Primo
Methodology
;
2024

Abstract

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.
2024
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
aerospace printed circuit board manufacturing
automated optical inspection
deep learning
mask R-CNN
open source dataset
printed circuit board defect detection
SMT component soldering
File in questo prodotto:
File Dimensione Formato  
jmmp-08-00117.pdf

accesso aperto

Licenza: Creative commons
Dimensione 14.3 MB
Formato Adobe PDF
14.3 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/519134
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact