/answers/how-to-inspect-bicycles-at-final-assembly-with-computer-vision/index.md · 42 lines
---
title: "How to inspect bicycles at final assembly with computer vision"
description: "A camera station at the end of the assembly line looks at each bike and flags missing or loose parts, crooked handlebars or seats, cables routed the wrong way, missing reflectors or caps, paint chips, scratches and decals out of place for a person to check. Each flag is saved with a photo and the model and frame number, so repeat problems point back to a station or a parts lot. A trained mechanic decides every pass or fix, and the usual torque, brake and ride checks stay in place."
url: https://lidvizion.ai/answers/how-to-inspect-bicycles-at-final-assembly-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
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# How can a bicycle maker or assembler use computer vision to check bikes before they are boxed?
A camera station at the end of the assembly line looks at each bike and flags missing or loose parts, crooked handlebars or seats, cables routed the wrong way, missing reflectors or caps, paint chips, scratches and decals out of place for a person to check. Each flag is saved with a photo and the model and frame number, so repeat problems point back to a station or a parts lot. A trained mechanic decides every pass or fix, and the usual torque, brake and ride checks stay in place.
## What this means in practice
- A few fixed cameras around the last station take pictures of each bike from both sides, the front and the top, before it is boxed or handed over.
- The model is trained on the clients own models and builds. It flags missing or loose parts, missing reflectors, caps or bells, cables or housings routed the wrong way, crooked handlebars, stems or seats, paint chips, scratches, and decals that are missing or out of place.
- Each flag is saved with a photo, the model, the frame number and the time, so the team can see if one station, shift or parts lot keeps causing the same problem.
- A trained mechanic checks every flagged bike and decides whether it passes or gets fixed. The cameras point at the bikes, not at workers, and any people caught in view are blurred.
- Start with one line and one model, compare the camera flags with what the final checkers find for a few weeks, and keep the existing torque, brake, wheel, ride and safety checks in place.
## 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
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- [How can an envelope or mailer maker use computer vision to inspect products on the line?](https://lidvizion.ai/answers/how-to-inspect-envelopes-and-mailers-with-computer-vision/)
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