What does a clean challenge test prove? At acceptance, known-bad units, for example trays with one item removed, are passed through and every one should be rejected. A run with no misses shows the station catches that fault. It cannot show the miss rate is zero: a finite test only bounds it. Using the Wilson method in NIST’s handbook for a proportion (NIST e-Handbook, 7.2.4.1), a run of n challenges with no misses gives a one-sided 95 % upper bound of z² / (n + z²), with z = 1.645.
Example: what a zero-miss challenge test can and cannot claim (one-sided 95 % Wilson bound)| Challenge units passed | Misses | 95 % upper bound on the miss rate | What it supports |
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| 30 | 0 | up to about 8.3 % | Shows the station can catch the fault; says little about how often it misses |
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| 100 | 0 | up to about 2.6 % | A reasonable start-up challenge for one fault type |
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| 300 | 0 | up to about 0.9 % | A stronger acceptance claim, usually built up over shifts |
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| 1,000 | 0 | up to about 0.27 % | Typically only reached by counting challenge passes over weeks |
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The practical rule: decide the claim first, then size the challenge test, and keep counting challenge passes after go-live so the evidence grows with every shift.
Worked example: speed and motion blur. An item moving during the exposure smears by speed × exposure time. Smear blurs the outlines a counting tool separates touching items by, so the exposure is chosen from the conveyor speed. The figures below are arithmetic, for planning.
Example: motion blur = speed × exposure| Conveyor speed | Exposure time | Smear on the item | What it means |
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| 0.5 m/s | 200 µs | 0.1 mm | Sharp enough for counting and presence of most items |
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| 1.0 m/s | 1 ms | 1.0 mm | Outlines smear; touching items merge; shorten exposure and add light |
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| 2.0 m/s | 100 µs | 0.2 mm | Needs strong, often strobed, lighting |
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Which tool does which count?
Vision sensors and smart cameras differ mainly in their tools. HIKROBOT’s own product pages list, for example, existence, count and measurement tools on the SC1000 (HIKROBOT SC1000), colour count and recognition on the SC2000E (HIKROBOT SC2000E), and learning-based and multi-object counting on the SC3000X (HIKROBOT SC3000X). Glue presence is often checked with UV-fluorescent glue under UV light, which HIKROBOT’s light catalogue describes (HIKROBOT light catalogue).
Matching the counting job to the device| Device class (HIKROBOT examples) | Counting and presence tools listed by the vendor | Typical fit |
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| SC1000 vision sensor | Existence, count, measurement, category recognition; no OCR or code reading | One check on a stable product, such as a scoop in a tin |
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| SC2000E colour vision sensor | Colour measurement, size and count; colour recognition; OCR with character comparison | Items told apart by colour, such as a coloured cap or insert |
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| SC3000X smart camera | Learning-based count, multi-object count, deep-learning classification and detection, anomaly detection | Irregular items such as baked goods, or several item types in one view |
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| Camera with VisionMaster on an industrial PC | Full tool set, several cameras, recipes per SKU | Kits and assemblies with many locations and variants |
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How acceptance is measured
- Miss rate (false accept): incomplete or short-counted units passed as good. Bounded by the challenge test above.
- False reject rate: good units rejected, counted over a production run and reviewed from the saved images.
- Reject confirmation: every rejected unit seen leaving the line by a sensor; a missing confirmation stops the line.
Counts and the law in South Africa
Where the quantity marked on a pack is a count, the count is the quantity. South Africa’s Legal Metrology Regulations require prepackages to comply with SANS 289, take their tolerances from SANS 458, and say the NRCS may not permit the sale of prepackages deficient of the quantity marked (Legal Metrology Regulations 2018). A camera count before closing, or a checkweigher after it, is how a packer shows each pack holds what it says.