The Challenge We Faced

A global Fast-Moving Consumer Goods (FMCG) enterprise - shipping thousands of packaged products per hour - struggled to guarantee consistent quality across an ever-expanding range of box sizes and configurations. Traditional vision-based Quality Assurance (QA) caught glaring defects, but frequent format changes, fast-moving lines, and variable packaging materials allowed subtle dimensional errors and minor surface damage to slip through undetected. Compounding the issue:



1. Conventional off-site data processing risked slowing the line or causing delays if network connectivity lagged.

2. Operators faced manual efforts to update manifests for each box type, introducing the risk of errors and inventory mismatches.

3. Rigid inspection thresholds assumed a single SKU line and had to be recalibrated whenever a new SKU was introduced.

Our customer needed a system capable of precise, real-time shape measurement and surface damage detection - all while integrating seamlessly with their established manufacturing execution software and gaining the capability to work with multiple SKUs on a single conveyor lane seamlessly.

Our Approach

We designed a comprehensive edge-based solution that combined 3D sensors for dimensional verification with RGB cameras for surface inspection. This platform provided:



1. Real-time scanning:

   • Dimension estimation using high-resolution point clouds helped to detect minuscule deviations in length, width, and height - even when switching rapidly between different box sizes.

   • Each package was photographed from multiple angles to spot tears, dents, label misprints, scuffs, or any other damage.

   • Automated reference checks on a known standard minimised manual intervention and calibration, ensuring consistent accuracy as SKU formats changed.


     
     

2. Edge processing:

   • All scanning and image analysis occurred locally, reducing latency and eliminating dependence on intermittent network connections. This eliminated the need for expensive, high-spec iPCs (Industrial PC).

   • Packages flagged as out-of-spec triggered automated sorting lines, separating defective or dimensionally incorrect items before they proceeded downstream.


     
     

3. Seamless integration with existing systems:

   • An API-based interface updated the facility’s existing software with each package’s exact dimensions and QA results, creating a live “manifest” for every shift.

   • The solution fits onto existing conveyors and tied into the company’s data infrastructure without needing a full-scale re-engineering effort.

A Future-Proof Inspection Architecture

The FMCG giant had strict requirements around throughput, reliability, and extensibility. Our response included:



1. High-fidelity 3D cameras:

   They captured dense point clouds for different conveyor heights and speeds on varying packaging materials. Our internal algorithms filtered noise from movement or inconsistent conditions.


   
   

2. Sophisticated yet lightweight AI models:
   Instead of running large, complex vision models that might bog down local hardware, we optimised the damage detection pipeline and models for edge-grade processors, ensuring real-time results without sacrificing accuracy.


   
   

3. Automated updates and model refinements:
   The system learned the new “normal” dimensions whenever a new box style was introduced. Operators only needed to confirm the baseline once, after which the software continuously adapted to slight variations.


   
   

4. Intuitive dashboards and alerts:


   Operators viewed pass/fail rates and live camera feeds on a centralised interface. If the system detected unusual spikes - eg, an uptick in corner tears - it flagged the line for immediate operator review.