/answers/how-to-inspect-rubber-seals-and-gaskets-with-computer-vision/index.md · 42 lines
---
title: "How to inspect rubber seals and gaskets with computer vision"
description: "Feed parts past a camera with backlighting or steady top lighting, then use a model trained on the plant own part images to mark likely flash, cuts, nicks, voids, short fills, trapped debris, surface blemishes and parts that look out of shape. Each mark is tied to the part number, mold and cavity where the tool tracks it, so the process tech can spot a problem early and a trained inspector can decide whether to pass, trim or scrap the part. The model only flags what the camera can see; it does not replace dimensional, hardness or leak tests, and people make every release call."
url: https://lidvizion.ai/answers/how-to-inspect-rubber-seals-and-gaskets-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Direct answers](https://lidvizion.ai/answers/)
# How can a rubber parts molder use computer vision to check seals, O-rings and gaskets?
Feed parts past a camera with backlighting or steady top lighting, then use a model trained on the plant own part images to mark likely flash, cuts, nicks, voids, short fills, trapped debris, surface blemishes and parts that look out of shape. Each mark is tied to the part number, mold and cavity where the tool tracks it, so the process tech can spot a problem early and a trained inspector can decide whether to pass, trim or scrap the part. The model only flags what the camera can see; it does not replace dimensional, hardness or leak tests, and people make every release call.
## What this means in practice
- Set up a fixed camera with backlighting or steady top lighting at the inspection point
- Collect images of parts that inspectors have already passed or rejected, for each part number and compound
- Label the defect types the quality team tracks, plus good examples of each part
- Send flagged parts to a trained inspector and log flags by part number, mold and cavity
- Add reviewed images back into training whenever a new part, mold or compound comes in
## How Lid Vizion approaches it
We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.
## More on Automation & custom AI
- [How can a metal stamping shop use computer vision to check parts as they come off the press?](https://lidvizion.ai/answers/how-to-inspect-stamped-sheet-metal-parts-with-computer-vision/)
- [How can a dealership, rental branch or fleet yard use computer vision to check which vehicles are on the lot?](https://lidvizion.ai/answers/how-to-audit-vehicle-lot-inventory-with-computer-vision/)
- [How can a garment factory use computer vision to check finished pieces before packing?](https://lidvizion.ai/answers/how-to-check-sewn-garments-with-computer-vision/)
[Compare services](https://lidvizion.ai/services/) · [Use a planning tool](https://lidvizion.ai/tools/) · [Explore workflow use cases](https://lidvizion.ai/use-cases/) · [More direct answers](https://lidvizion.ai/answers/)
Talk it through
## Have a version of this question inside your company?
Bring the decision, the constraints, and what a good outcome looks like.
[Talk through the decision](https://lidvizion.ai/contact/?need=ai-workflow&from=%2Fanswers%2Fhow-to-inspect-rubber-seals-and-gaskets-with-computer-vision%2F#write) · [Book a call](https://calendar.app.google/bB26LdA9e2gmGFp69)