Start / Lösungen / Etikettenprüfung
Etikettenprüfung
MarshallAI überprüft die Anwesenheit, Position, Druckqualität und Farbe der Etiketten auf jeder Einheit bei voller Liniengeschwindigkeit. Produkt-/Artikelnummernänderungen werden automatisch erkannt, ohne dass eine Umstellung zwischen Marken oder Chargen erforderlich ist.
Keine Weiterbildung zwischen den Chargen
Eine neue SKU wird aktiv, und die Inspektion beginnt. Es sind keine Referenzbilder mehr erforderlich, keine Konfigurationsfenster müssen neu programmiert werden.
Erkennt subtile Druckfehler
Flecken, Farbveränderungen, fehlende Designelemente sowie verzerrte oder unordentliche Etiketten.
99,99995%-ige Erkennungsgenauigkeit
Bei voller Liniengeschwindigkeit durchgeführt.
2500+ Einheiten pro Minute
Komplexer Inspektion mit voller Liniengeschwindigkeit. Die Leistung kann mit der Verarbeitungshardware skalieren werden.
Verringern Sie Rückrufaktionen und Reklamationen
Sicherstellung der Compliance in allen Märkten
Verwenden Sie nicht die Funktion „Hold-For-Inspect“ (HFI)
What Can Go Wrong With a Label
A label failure can occur due to several reasons:
- Presence and placement. A missing label, or one applied askew, upside down, or in the wrong position, reaches the point of sale looking unfinished or wrong.
- Print quality. Smudged ink, low-contrast printing, creases, tears, and missing design elements degrade both readability and shelf appeal.
- Color and brand accuracy. A label printed with the wrong color, or a print run that drifts from the approved reference over time, breaks brand consistency at the exact moment a customer is deciding to buy.
- Content accuracy. Best-before dates, batch codes, and barcodes that are unreadable, incorrect, or missing create compliance and traceability problems long after the product has left the plant.
Any one of these can become a hold-for-inspection situation or worse yet; a regulatory or recall issue.
How MarshallAI Verifies Labels
MarshallAI checks a label the way a person would — for what’s actually wrong with it, not just how far its pixels drift from a stored reference — using our advanced AFSA platform.
- No retraining on brand or packaging changes. Every SKU your line runs is already known to the model. When a changeover happens, inspection continues without a retraining step or a new set of reference images to capture.
- Tunable tolerance. The system can distinguish a meaningful defect from a passable cosmetic variation.
- Print, color, and content in one pass. Label presence and position, print quality, color verification, and OCR of best-before dates, batch codes, 1D barcodes, and 2D codes (DataMatrix, QR) all run as part of the same inspection sequence.
- Millisecond latency edge processing. Inspection runs entirely on-site, next to the line, keeping pace with full production speed.
Case studies
-
Mastering QA in High-Mix Manufacturing: Rapid Changeovers and >99% Accuracy at TaerosolContract manufacturing and frequent product changeovers used to mean a constant struggle with QA bottlenecks. Discover how Taerosol future-proofed their cosmetics line with a rapidly adaptable AI system that catches over 99% of complex label and packaging defects.
Cosmetic manufacturing Quality assurance
-
Eliminating Rogue Cans: High-Speed QA in Beverage ManufacturingA global beverage manufacturer spent 15 years trying to reliably intercept “rogue cans” on their high-speed filling lines. Discover how MarshallAI deployed a minimal latency edge vision system to inspect 2,500 cans per minute, preventing mismatched products and costly mechanical jams with near-perfect precision.
Beverage industry Quality assurance
Questions & Answers
Does MarshallAI need to be retrained when we introduce a new label or packaging design?
No. Every SKU is already modeled in advance, so a new design is recognized and inspected from the first unit — there’s no retraining step or downtime while the system learns it.
What happens when a faulty label 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 two labels apart that only differ by one small detail?
Yes. The system verifies a label’s full identity and print quality rather than comparing against a single similarity threshold, so it catches differences that a coarser pattern-match would treat as acceptable.
Does it read barcodes and 2D codes on labels?
Yes, 1D barcodes and 2D codes such as DataMatrix and QR are read and verified in the same pass as the rest of the label.
Does inspection data leave our facility?
No. Processing runs entirely on-site. Label images and production data stay on your network.
