Application selection example
Application route for scratches, burrs, dents and reflective metal surface checks using lighting-first machine vision selection. This in-house example proposes 3 acceptance checks and 4 RFQ inputs. It does not report completed customer testing or achieved performance.
Best used when the metal finish changes from batch to batch and the lighting route must be proven before quoting.
Reflective metal surfaces can hide scratches and burrs unless the lighting geometry is matched to the defect direction and part movement.
Start with bar, coaxial or dome lighting tests, then match the industrial camera, lens and trigger method to the verified contrast route.
3 lighting geometries compared before model selection
Case decision frame
Worked examples explain the problem, assumptions, component candidates and evidence a project needs. Use these four fields to prepare a test plan for your own application.
Reflective metal surfaces can hide scratches and burrs unless the lighting geometry is matched to the defect direction and part movement.
3 lighting geometries compared before model selection Worst-case defect samples photographed at line speed
Bar / coaxial / dome lighting test set + Industrial 2D camera + Low-distortion lens + Trigger and reject output
Defect sample photo set, Lighting-angle test note, Line-speed constraint note
Inspection workflow
The right product family depends on measurable samples, line conditions and acceptance criteria. Use this workflow to move from application idea to testable project evidence.
Example boundary
These routes show how a selection decision is reached and what is checked before acceptance. Numeric values and planning windows are example targets, not achieved results or promised lead times. These are not audited performance figures, not a customer reference list, and not a claim that any particular buyer ran this route.
Not applicable. These routes are illustrative — worked examples of how a selection decision is reached, written in house. No engagement, buyer or site sits behind any of them, so there is no party whose permission could be sought. This is not a record of consent obtained; it is a record that consent has no subject here.
Application visuals are illustrative and are not offered as photographs of a customer installation. Numeric checks and planning windows are example targets, not measured outcomes or promised lead times.
Related product families
Ring, bar, coaxial, dome, backlight, dark-field and line-light routes matched to defect contrast, edge clarity and part surface behavior.
Product routeArea-scan, USB3, GigE, global-shutter, high-speed, high-resolution and special-spectrum industrial cameras for machine vision.
Product routeStructured-light 3D sensors and line-laser profile measurement routes for height, profile and surface geometry checks.
Related solution and selection pages
Build automated visual inspection systems for defect detection, presence checks, surface inspection, orientation, measurement and repeatable pass/fail output.
ResourceSelect lighting for reflective metal scratch, burr and surface defect inspection by glare behavior, defect direction, camera angle and acceptance evidence.
ResourceChoose machine vision lighting by surface finish, defect direction, camera angle, working distance and acceptance evidence instead of choosing by light shape alone.
ResourceCompare ring, bar, dome, coaxial, backlight and line lighting types by surface behavior, defect contrast and installation constraints.
ResourceA beginner-friendly guide to choosing machine vision lighting by contrast, surface behavior and defect type.
ResourceCompare backlight and coaxial machine vision lighting for silhouette measurement, flat reflective surfaces, printed marks and surface feature contrast.
Application RFQ
Send sample images, line speed, tolerance and the current failure mode. We will map the application to camera, lighting, lens, reader, 3D or smart camera routes.
Request engineering RFQ| # | Proposed acceptance check to validate |
|---|---|
| 1 | 3 lighting geometries compared before model selection |
| 2 | Worst-case defect samples photographed at line speed |
| 3 | False-reject target agreed before fixture release |
Application FAQ
No. This is an in-house application selection example for automotive reflective metal inspection. No customer engagement, buyer or site sits behind it. The component route, sample requirements and numeric acceptance targets are proposals to validate, not achieved results.
Send defect sample photo set, lighting-angle test note, line-speed constraint note, fixture mounting envelope. Include good and bad samples whenever possible so engineering can test the route before recommending hardware.
Machine Vision Lighting, Industrial 2D Cameras, 3D Vision Cameras are the first product families to review, but the final route depends on sample images, speed, tolerance and installation space.
Send part photos or drawings, target defect or measurement goal, field of view, working distance, line speed, accuracy target, lighting limits and any current camera, lens, light, barcode reader or competitor model.
Use 2D when contrast, edges, labels or position are enough to judge the part. Use 3D when height, profile, gap, volume, weld shape or surface geometry decides pass or fail.
Start from the defect and material surface instead of the camera model. Backlight helps edge measurement, coaxial and dome lighting help reflective surfaces, and bar or ring lighting often works for general presence and defect checks.
