Enhancing AOI with AI for Printed Circuit Board Assembly – A Comprehensive Industry Study
The integration of Artificial Intelligence (AI) with Automated Optical Inspection (AOI) systems holds significant potential for improving the accuracy and efficiency of defect detection in Printed Circuit Board Assembly (PCBA). This paper presents the findings of an industry-wide study conducted by the International Electronics Manufacturing Initiative (iNEMI) on the adoption and enhancement of AI in AOI systems. Building on the results of Phase 1, which established performance metrics and identified key challenges, Phase 2 involved experimental evaluations to provide industry-wide recommendations. The study highlights the benefits, challenges, and future directions for AI-enhanced AOI systems.
Authors
- Kah Fai Leong (ORCID: https://orcid.org/0000-0002-9302-1163)
- Jörg Richstein
- Daniel S.W. Tan (ORCID: https://orcid.org/0000-0002-6514-6786)
- Chwee Liong Tee
- Zambri Samsudin
- Wayne Zhang
- C ZHU
- Mehdi Hamid
- Feng Xue (ORCID: https://orcid.org/0000-0003-4613-7785)
- Haley Fu
- Yassin Roslan
- Aersi Aierzhati
- Stephan Pimer
- Romain Roux
- Philip Aguilar Reyes
- Tatu Qvist
- Harri Sievola
Institutions
- IBM (United States) (US)
- Singapore Institute of Technology (SG)
- Nokia (Finland) (FI)
- Advanced Digital Sciences Center (SG)
- IBM Research (China) (CN)
- Intel (Malaysia) (MY)
- PDF Solutions (United States) (US)
- Jabil (United States) (US)
Publication Details
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/iemt61324.2024.10875165
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00