Vision AI Deployment Checklist for Manufacturing

A practical 20-point checklist built from our experience deploying computer vision inspection systems on real factory floors. Every item comes from a lesson we learned the hard way.

Overview

From camera setup to model maintenance, covered in 20 points

We built this checklist for manufacturing engineers and plant managers who are deploying vision AI inspection systems for the first time, or improving an existing setup. It covers every phase from hardware selection through ongoing model maintenance, organized into five clear categories.

What is Covered

Checklist Categories

Camera and Lighting Setup

5 points

Verify lighting consistency across shifts

Validate camera field of view covers full inspection area

Confirm image resolution meets defect detection requirements

+ 2 more in the full checklist

Model Training and Validation

5 points

Define minimum acceptable inference speed

Establish ground truth dataset with expert-labeled samples

Test model accuracy against edge cases and rare defect types

+ 2 more in the full checklist

Edge Hardware Selection

4 points

Match compute capacity to inference workload requirements

Plan for thermal management in factory environments

+ 2 more in the full checklist

Integration with Production Line

3 points

Map trigger signals and timing with line speed

Define reject handling and escalation workflows

+ 1 more in the full checklist

Monitoring and Maintenance

3 points

Plan for model retraining pipeline

Set up drift detection alerts for accuracy degradation

+ 1 more in the full checklist

Download the Full Checklist

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