Automated verification of cap, seal, label, fill level, and batch code on a production conveyor. An AI-enabled inspection solution combining controlled image capture, automated decisions, and traceable quality records.
FMCG Packaging
Computer Vision
Packaging Inspection & Defect Rejection
Edge IPC, Area-scan Cameras, Deep-learning Models, PLC Integration
High-speed lubricant packaging lines require consistent checks for missing or incorrect caps, damaged seals, and low fill levels.
Manual inspection cannot reliably review every single bottle at production speed without causing bottlenecks or allowing defects to slip through to the customer.
Furthermore, quality control teams need concrete image evidence, immediate exception handling, and batch-wise traceability for corrective action. The overarching goal was to completely automate the inspection with consistent decisions and traceable records.
A clear operational flow combining automated inspection, configurable decisions, and accountable human oversight.
Industrial area-scan cameras and strobed, controlled lighting are installed at critical inspection stations along the conveyor belt. When a bottle passes the trigger point, a high-resolution image is instantly captured without slowing the line.
Deep-learning computer vision models instantly detect bottle presence, orientation, cap fitment, seal integrity, and visible packaging defects. The AI also measures fill levels and verifies label positions, artwork, barcodes, and batch/date codes.
Confidence and tolerance workflow rules determine the immediate next action. If a defect is detected, the Edge IPC sends a signal to a PLC-integrated pneumatic rejector which swiftly kicks the bad bottle off the line.
The system stores inspection images, exact defect reasons, production line data, product SKUs, and timestamps. This data is fed into a recipe management and production dashboard for continuous quality monitoring.
A modular edge-AI architecture connects industrial imaging with real-time decisions, automation and quality reporting.
| Vision | Industrial area-scan cameras and strobed lighting |
|---|---|
| Edge AI | Edge industrial PC with AI inference |
| Decision | Computer vision / deep-learning models |
| Automation | PLC integration and pneumatic rejector |
| Insights | Recipe management and production dashboard |
The automated inspection solution transformed the packaging line's reliability and operational throughput.
Enables 100% consistent inspection at maximum conveyor speed, drastically shortening the time between defect capture and operational action.
Guarantees the immediate removal of packaging defects through highly-responsive, PLC-integrated pneumatic rejection systems.
Creates structured, searchable records and dashboards for reporting, audit, and follow-up by exact defect category and SKU.
Eliminates the bottleneck of manual checking, allowing quality teams to focus purely on exceptions, verification, and process improvement.
