Manufacturing & Industrial Vision// topic
Visual inspection and defect detection
In short
Whether a camera can actually judge your part: what defect classes are learnable, how few images you can start with, and what a false reject costs when the line does not stop for it.
4 pages
definitions
- False reject rate: what the line feels, not the accuracy on the slideA 1% false reject rate sounds like rounding. At 1,200 parts an hour it is 96 good parts a shift and over an hour of somebody re-checking them.definition6 min
- The anomaly score is a ranking; the threshold is a business decisionThe score orders parts by how far they sit from normal. It carries no units, no probability and no severity — which is why the threshold belongs to quality, not to engineering.definition6 min
- The golden sample is a decision record, not just a good partThe part in the drawer is the easy half. Its record — revision, attribute, approver, date, recheck trigger — is what an automated inspection inherits.definition6 min
- Writing the defect class list your inspection will be graded againstEvery class needs a name, a definition, a severity, a disposition and a minimum size. Classes two inspectors cannot separate produce a confusion matrix nobody can act on.definition6 min
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