Rivet inspection: Datasets & Models
Automated visual inspection of rivets on aerospace fuselage, wing, and panel assemblies to flag defects like missing, loose, or improperly seated rivets. Uses object detection to locate and classify each rivet and its condition in captured images.
Rivet inspection
This workflow runs rivet defect detection on aerospace assemblies, locating each rivet in an image and classifying its condition as properly installed or defective, including missing, loose, or improperly seated rivets. It accepts still images or video frames captured by handheld cameras, fixed inspection rigs, or robotic arms scanning fuselage skins, wing panels, and structural joints.
Try it out
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Why automate rivet inspection
Manual rivet inspection on an airframe means an inspector visually checking thousands of fasteners per assembly, a slow and fatigue-prone task where a single missed or improperly seated rivet can compromise structural integrity. Automating rivet defect detection gives consistent, repeatable evaluation of every fastener without inspector-to-inspector variation, and it captures a timestamped image record for traceability and audit. For aerospace teams under tight quality and compliance requirements, this reduces rework caught late in production and helps catch defects before assemblies move downstream. It also frees skilled inspectors to focus on adjudicating flagged cases rather than scanning acres of rivet lines.
Key benefits
Teams get faster inspection cycles, complete coverage of every rivet rather than sampled spot checks, and a searchable image trail for each part. The models run against existing inspection cameras and robotic or fixed-mount setups, so there is no need to replace hardware, and detection scales from a single station to full production lines. Built on RF-DETR, the workflow delivers strong accuracy on small, densely packed fasteners while remaining straightforward to retrain as new part geometries and defect types appear.
How to use it
- Upload an image: Drop any photo into the widget above to try rivet inspection for free, right on this page.
- Preview instant results: The model detects rivet, missing rivet, cracked rivet head, protruding rivet, countersunk rivet within seconds and returns an annotated image with structured predictions, so you can immediately see how well it works. Adjust the detection classes and re-run until the results fit your scenario.
- Like what you see?: With a free Roboflow account, you can deploy this workflow with the Serverless Cloud API, customize it in your workspace, or train RF-DETR on your own images for production accuracy.
- Get started for free: No code or training data required to begin: upload, review the results, and make it part of your stack in a single click.
Recommended model for rivet inspection
RF-DETR is state of the art for real-time object detection, instance segmentation, and keypoint detection, with higher accuracy and lower latency than comparable models, and it's Apache 2.0 licensed. When you're ready to build a production model for rivet inspection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Rivet Inspection project to Roboflow Agent.