Electronics visual inspection
Help inspectors focus on the electronics that need a closer look
An anonymized high-mix electronics engagement using edge vision, product context and human review for uncertain results.
The inspection challenge
Different board variants and small defects created a demanding inspection task. The published brief describes inconsistent manual performance and a review burden in the earlier inspection workflow. Image quality, product identity and reliable defect labels had to be addressed together.
What NeoBram delivered
The engagement used an approved camera and edge-compute setup to evaluate selected defect classes in the correct product context. Uncertain or disputed results went to people. Reviewed events and operator feedback supported traceability and controlled model changes. The manufacturer retained quality-release authority.
What the engagement reported
The brief states 99.4 percent defect detection, a tenfold reduction in customer escapes, a threefold inspector-throughput change and 65 percent fewer false calls. These are non-public engagement figures. The public account lacks the class distribution, denominator, held-out test details and signed acceptance record needed to independently evaluate them. A single aggregate percentage does not establish performance on every rare defect or product variant.
Test the economics of your inspection point
Measure customer escapes, internal rejects, false calls and review time separately. Test across shifts, product changes and lighting conditions. Compare total operator effort, including uncertain-case review, with the current method. Camera hardware, integration and continuing evaluation belong in the investment case. Any decision to automate rejection requires its own engineering and quality approval; a successful detection demo does not authorize it.
More clarity
Questions and answers
Can the same model inspect all our products?
That must be tested. Product variation can change the required data, model configuration and acceptance thresholds.
Does 99.4 percent mean 99.4 percent of every defect type?
The published evidence does not establish that. Ask for performance by defect class and operating condition.
Start with one business problem