The team faced defect escape, limited inspection capacity, and tension between throughput and quality. Manual checks were variable and difficult to scale across shifts. Manual inspection could not keep pace with line speed, and detected defects lacked clear explanations, making root-cause analysis slow and inconsistent.

Key challenges included:

• Defect escape due to limited inspection coverage
• Manual inspection unable to scale with throughput
• Inconsistent quality decisions across shifts
• Late detection of defects during production
• Lack of reasoning behind detected defects

Our approach includes a computer vision–based inspection system directly on the production line. The system inspects every product in real time, detecting surface, dimensional, and assembly-related defects. Detected defects are not only flagged, but also contextualized using production parameters, timing, and machine state to support reasoning and root-cause analysis.

The solution enabled:

• Real-time inspection of every product
• Early defect detection during production
• Explainable defect reasoning
• Consistent quality decisions across shifts
• Integration with quality and MES systems

Systems designed for demanding production environments with a focus on documented reliability.

1. 1Computer vision inspects products in real time
2. 2Defects are detected and classified instantly
3. 3Production context is linked to each defect
4. 4Quality teams receive explainable insights

• More defects caught than manual-only inspection
• 2× improvement in early-stage defect detection
• Reduced defect escape to downstream processes
• Faster root-cause identification

• Higher product quality
• Reduced rework and scrap
• Stable throughput without manual bottlenecks
• Trustworthy, explainable quality decisions