Weiss, E.; Caplan, S.; Horn, K.; Sharabi, M. Real-Time Defect Detection in Electronic Components during Assembly through Deep Learning. Electronics2024, 13, 1551.
Weiss, E.; Caplan, S.; Horn, K.; Sharabi, M. Real-Time Defect Detection in Electronic Components during Assembly through Deep Learning. Electronics 2024, 13, 1551.
Weiss, E.; Caplan, S.; Horn, K.; Sharabi, M. Real-Time Defect Detection in Electronic Components during Assembly through Deep Learning. Electronics2024, 13, 1551.
Weiss, E.; Caplan, S.; Horn, K.; Sharabi, M. Real-Time Defect Detection in Electronic Components during Assembly through Deep Learning. Electronics 2024, 13, 1551.
Abstract
This paper presents a groundbreaking approach to real-time image processing in electronic component assembly, enhancing quality control in manufacturing. By capturing images from pick and place machines between component pickup and mounting, defects are identified and addressed in-line, significantly reducing the likelihood of defective products. Leveraging fast network protocols like gRPC and orchestration with Kubernetes, along with C++ programming and TensorFlow, this method achieves an average turnaround time of less than 5 milliseconds. Tested on 20 live production machines, it ensures compliance with IPC-A-610, and IPC-STD-J-001 standards while optimizing production efficiency and reliability.
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
