Computer-Vision Feasibility for Quality Inspection: Questions to Answer First
A feasibility framework for evaluating whether computer vision can support a real quality-inspection workflow before production deployment.
Computer vision quality inspection begins with the operating environment, not the model. The useful first question is what a person currently observes, what counts as a defect or exception and what action should follow when the system identifies one.
Feasibility work should examine the physical conditions around the workflow: camera position, lighting, product variation, line speed, available examples and the cost of different error types. These details affect what can be detected and how the system should fit into operator decisions.
A practical pilot defines a narrow first use case, a representative evaluation set and a review path for uncertain results. It should also consider integration requirements, edge or cloud processing constraints and how the team will monitor the system after launch.
The outcome of feasibility is a decision-ready plan: whether to proceed, what evidence is still needed and which architecture best supports the environment. That is more useful than treating a demonstration as proof of production readiness.