Technical Paper
Prevention of Operational Errors in Semi-Automatic Riveters by Machine Vision Systems Using Deep Learning
2024-03-05
2024-01-1944
This paper reports the development of an operation support system for production equipment using image processing with deep learning. Semi-automatic riveters are used to attach small parts to skin panels, and they involve manual positioning followed by automated drilling and fastening. The operator watches a monitor showing the processing area, and two types of failure may arise because of human error. First, the operator should locate the correct position on the skin panel by looking at markers painted thereon but may mistakenly cause the equipment to drill at an incorrect position. Second, the operator should prevent the equipment from fastening if they see chips around a hole after drilling but may overlook the chips; chips remaining around a drilled hole may cause the fastener to be inserted into the hole and fastened at an angle, which can result in the whole panel having to be scrapped.