2023/12/14 by Audrey G. Chung, Francis Li, Chung, Audrey +7
Biochemistry, Genetics and Molecular Biology · Engineering · #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Processing Techniques and Applications #Industrial Vision Systems and Defect Detection
paper · pdf · doi:10.48550/arxiv.2312.09232
openalex publication_date 2023/12/14 · openalex created_date 2023/12/16 · openalex updated_date 2026/07/28
As electronics manufacturers continue to face pressure to increase production efficiency amid difficulties with supply chains and labour shortages, many printed circuit board assembly (PCBA) manufacturers have begun to invest in automation and technological innovations to remain competitive. One such method is to leverage artificial intelligence (AI) to greatly augment existing manufacturing processes. In this paper, we present the DarwinAI Visual Quality Inspection (DVQI) system, a hardware-integration artificial intelligence system for the automated inspection of printed circuit board assembly defects in an electronics manufacturing environment. The DVQI system enables multi-task inspection via minimal programming and setup for manufacturing engineers while improving cycle time relative to manual inspection. We also present a case study of the deployed DVQI system's performance and impact for a top electronics manufacturer.