Koti / Ratkaisut / Vieraiden purkkien havaitseminen
Stop the One Wrong Can Before It Ships
Verify the identity of every can on your filling line. MarshallAI catches foreign products and mixed labels from the very first can of a new batch, with no re-programming and no learning period.
Can be combined with our Best Before Date inspection and our Label inspection solution for label presence and condition inspection.
Our Rogue Can Detector also detects fallen and damaged cans.
See all solutions for beverage industry
Minimize recalls and complaints
Ensure compliance in every market
Avoid Hold-For-Inspect(HFI)
Meet us at BrauBeviale 2026 on the 10-12th of November | Hall 10 stand 10-139. Book a live demo.
Zero Changeover Downtime: Recognizes each SKU automatically as it starts running. No operator “train” step, no re-teaching the system between batches. Perfect for even small batches.
Protected From Can One: Flags a mismatched can the moment it appears. No ramp-up period or sample run needed to learn what’s “normal” before protection kicks in.
99.99995% Detection Accuracy: Holds this accuracy at full line speed, on every SKU.
2500+ Cans a Minute: Every can inspected. Performance can be scaled with processing hardware.
Fallen, misaligned and damaged can detection.
– Customer, beverage industry
Why Foreign / Rogue Cans Slip Past
A rogue can happens when an empty can meant for one product ends up on the wrong filling line — a domestic-market can filled with an export formulation, or a leftover can from the previous batch mixed into a new run.
Because SKUs in a portfolio can share near-identical can geometry and print design, the two cans can look almost identical to a traditional inspection system.
- Traditional label verifiers are not built to tell apart two versions of the same label with only a subtle formulation difference.
- Traditional systems can be hard to tune, tightening thresholds to catch subtle differences means risking more false rejects.
Rogue Can Detection: MarshallAI vs. Legacy Label Verifiers
| Operational Aspect | Legacy Label / Deco Verifiers | MarshallAI |
|---|---|---|
| Detection basis | Compares small area against a reference; flags deviation past a set threshold. | Verifies each can’s full product identity against the SKU that should be running |
| Near-identical SKU variants (e.g. domestic vs. export) | Prone to miss — differences can fall inside the pattern-matching tolerance. | Built to catch — trained on every SKU’s distinct signature, not just gross print differences. |
| New batch / SKU changeover | Operator triggers a “learn” step for the new label; protection relies on the previous batch’s memorized pattern until it’s retrained. | Recognizes the new SKU automatically — protected from the first can, no learning step. |
| Detection reliability | Depends on sample size and a sensitivity setting, trading off missed defects against false rejects. | 99.99995% accuracy, consistent across SKUs and runs. |
| Scope | Single-purpose module for label/deco inspection. | One station covers rogue can, fallen can, and damaged cans. |
Asiakastarinat
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Hylättyjen tölkkien karsiminen: Suurnopeuslaadunvarmistus juomateollisuudessaEräs maailmanlaajuinen juomavalmistaja yritti 15 vuoden ajan luotettavasti poimia “vialliset tölkit” pois nopeista täyttölinjoistaan. Lue, kuinka MarshallAI otti käyttöön viiveettömän reunanäkökamerajärjestelmän, joka tarkastaa 2 500 tölkkiä minuutissa ja estää lähes täydellisellä tarkkuudella tuotteiden virheellisen lajittelun sekä kalliit mekaaniset tukokset.
Juomateollisuus Laadunvarmistus
Questions & Answers
Does MarshallAI need to “learn” each new SKU before it can protect the line?
No. Every SKU in your portfolio is modeled in advance, so the system recognizes what’s running the moment a changeover happens. There’s no operator-triggered training step and no window where the line is unprotected.
What happens when a rogue/foreign can is detected?
We can issue an alert, halt the line or integrate with a rejection mechanism. Timelined statistics are also provided for total products and faulty products for OEE optimisation and root cause analysis.
Can it tell apart two versions of the same can — like a domestic and export variant?
Yes. This is exactly where MarshallAI excels. Because the model verifies a can’s full identity rather than comparing print patterns against a similarity threshold, it catches differences that fall below what pattern-matching systems are tuned to flag.
Does inspection data leave our facility?
No. Processing runs entirely on-site. Detection images and production data stay on your network.
Will this slow down our line or require a new SKU program for every product?
No. MarshallAI runs at full line speed: 2500+ cans a minute and handles SKU changeovers automatically, with no reconfiguration required.
