Customer Focus

Food processors, agri-packers, and FMCG companies in India focus on consistent quality, reduced wastage, and higher throughput. Operations and quality teams require an automated, objective grading system to replace manual sorting. The goal is to achieve uniform product standards, export-grade quality, and improved profitability while adapting seamlessly to existing conveyor-based processing lines.

Requirements

The customer required a visual grading solution to automatically inspect fruits and vegetables based on size, shape, color, surface defects, and ripeness. The system needed to function in real time on conveyor belts, integrate with existing sorting mechanisms, and provide standardized grading outputs with minimal human intervention.

Manual grading was subjective, inconsistent, and dependent on operator experience and fatigue. Variations in lighting, produce size, and seasonal quality impacted grading accuracy. High rejection rates and delayed sorting increased wastage and operational costs. Maintaining uniform quality standards across shifts and batches remained a major challenge.

Pain Points

• Inconsistent quality classification
• High product wastage
• Limited traceability of grading decisions

Lubi Electronics deployed an AI-driven Computer Vision grading system using deep learning–based image analysis and classification models. High-speed cameras inspect produce on moving conveyors and grade items in real time. The system ensures consistent quality standards, reduces manual dependency, and integrates with sorting actuators for automated segregation.

Solution Highlights

• AI-based size, color & defect detection
• Real-time grading on conveyors
• Edge AI for low-latency decisions