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

Author:

Fontana Gianmauro1ORCID,Calabrese Maurizio2ORCID,Agnusdei Leonardo2ORCID,Papadia Gabriele2ORCID,Del Prete Antonio2ORCID

Affiliation:

1. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing CNR-STIIMA, Via A. Corti 12, 20133 Milan, Italy

2. Department of Innovation Engineering, University of Salento, Via per Monteroni, 73100 Lecce, Italy

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.

Funder

spin-off of the University of Salento Advantech-LIKE S.r.l.

Publisher

MDPI AG

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