Visual Inspection System Design Checklist

Direct answer

Visual Inspection System Design Checklist

A visual inspection system should be designed from the reject decision backward. Define good/bad samples, target defect, tolerance, line speed, optics, lighting, trigger, I/O and acceptance tests before selecting hardware.

Where this matters

Start with the inspection condition.

A visual inspection system should be designed from the reject decision backward. Define good/bad samples, target defect, tolerance, line speed, optics, lighting, trigger, I/O and acceptance tests before selecting hardware.

Why projects fail

Confirm the limits that change hardware.

Lighting and fixture stability control most repeatability issues.

RFQ preparation

Send enough context for a real review.

Acceptance tests should be measurable before shipment.

What engineering should check

What this page should help teams decide.

Define pass and fail samples before hardware selection.
Lighting and fixture stability control most repeatability issues.
Acceptance tests should be measurable before shipment.

Related Deyi routes

Product families commonly involved.

Practical note

Start from the production decision.

The system should first define what output the line needs: pass, fail, measurement value, barcode result, coordinate, height profile or reject signal. This decision shapes camera count, lighting, software and I/O.

Practical note

Build a sample set before model selection.

A useful sample set includes good parts, clear failures, borderline cases and surface or position variation. Without these samples, the supplier cannot know whether the inspection rule will survive production variation.

Practical note

Treat lighting and fixture as system components.

Most unstable visual inspection systems fail because light geometry, fixture movement or part presentation changes the image. The design checklist should review light type, mounting angle, working distance, trigger timing and mechanical repeatability together.

Practical note

Write acceptance criteria before shipment.

Acceptance should define sample count, repeatability, false reject target, false pass target, read rate, measurement tolerance or station timing. These checks make the quote measurable instead of subjective.

How to test before buying

Use this guide as a pre-RFQ decision filter, not as a part-number shortcut.

Machine vision selection is usually stable when the project starts from the inspection condition instead of a catalog model. Before requesting a quote, define what must be detected or measured, how the part moves, what surface behavior affects contrast and which factory constraint cannot change.

Use this guide to translate the requirement into testable inputs: sample images, target tolerance, line speed, field of view, working distance, mounting envelope and the current failure mode. That gives the factory enough evidence to map the request to camera, lighting, optics, reader or 3D routes.

Decision checks

Three checks before locking the route.

01

Defect criteria

Define what must be rejected and what may pass.

02

Optics and lighting

Match lens, working distance, light geometry and fixture.

03

Trigger and speed

Exposure, trigger and line speed must fit the moving part.

Decision table

Use these data points to turn the concept into an RFQ-ready decision.

Factor	Practical rule	RFQ impact
Defect criteria	Define what must be rejected and what may pass.	Prevents vague visual standards.
Optics and lighting	Match lens, working distance, light geometry and fixture.	Creates stable image evidence.
Trigger and speed	Exposure, trigger and line speed must fit the moving part.	Reduces blur and missed captures.
Acceptance test	Use measurable repeatability, read-rate or false-pass checks.	Makes delivery review objective.

Application proof

Related delivery routes that make this selection decision concrete.

View all cases

Electronics inspection

PCB Connector Pin Presence Inspection

Small connector features require stable contrast, low distortion and repeatable part positioning before a pass/fail threshold can be trusted.

Automotive parts inspection

Automotive Metal Surface Defect Inspection

Reflective metal surfaces can hide scratches and burrs unless the lighting geometry is matched to the defect direction and part movement.

Textile and web inspection

Roll-to-Roll Web Defect Inspection

Wide moving material needs even illumination, encoder synchronization and enough line rate to avoid missing small defects.

Common mistakes

Problems that slow down selection.

Selecting by model number before the inspection target is measurable.
Treating lighting as an accessory instead of the main contrast-control tool.
Ignoring fixture stability, part variation and operator maintenance workflow.

Factory handoff

What Deyi Vision reviews after receiving the project details.

The factory route review starts by checking whether the image can be made stable with lighting and fixture control. Then the camera, lens, reader or 3D sensor route is sized against speed, resolution, interface and installation constraints.

If you already have a Keyence, Cognex, Basler, OPT, LMI, Hikrobot or barcode-reader reference, include it as a reference model. Deyi Vision uses it to understand the application class; final selection still depends on real samples and production limits.

Guide to RFQ

Have a real part, sample image or production constraint?

Use the guide to frame the question, then send the details so engineering can recommend a route.

Request engineering RFQ

Guide FAQ

Questions related to visual inspection system design checklist.

Ask engineering

What is the first step in visual inspection system design?

Define the production decision and the target defect or measurement before choosing a camera, lens, light or software tool.

Why do visual inspection systems fail in production?

Common causes are weak lighting contrast, unstable fixture position, unclear defect criteria, motion blur and missing acceptance tests.

What should be included in an inspection system RFQ?

Include part photos, good/bad samples, defect definition, tolerance, FOV, working distance, line speed, trigger method, I/O and acceptance criteria.