Challenge

Pastry quality control is performed manually by an operator at the forming machine outlet. The operator visually inspects each item and removes defects β€” filling leakage, deformation, integrity violations.

  • Subjective assessment depends on operator fatigue and attention
  • Manual inspection speed limits line throughput
  • Impossible to ensure 100% control at high production rates
  • No statistics on defect types and frequency

Solution

Three system configurations for different production volumes. Common architecture: industrial camera captures the product stream, neural network classifies each pastry, actuator automatically removes defective items from the conveyor.

  • Defect detection: filling leakage, deformation, integrity violations, foreign inclusions
  • Real-time neural network classification
  • Pneumatic ejector or pusher for defect removal
  • Three configurations: basic / standard / extended for different line speeds
  • Defect statistics accumulation with breakdown by defect type

Diagrams

Option A β€” pneumatic rejection system

Option A β€” pneumatic rejection system

Option B β€” cobot arm on conveyor

Option B β€” cobot arm on conveyor

Option B β€” delta robot (parallel manipulator)

Option B β€” delta robot (parallel manipulator)

Key Advantages

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100% inspection

Every item is inspected regardless of line speed or time of day.

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Defect analytics

Automatic defect type statistics β€” foundation for recipe and equipment improvement.

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Three configurations

Basic, standard and extended β€” choose by budget and throughput.

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Easy integration

Installed on existing line without production shutdown.

Technologies

  • Neural network defect classification
  • High-resolution industrial camera
  • Machine vision computing module
  • Pneumatic or mechanical rejection system
  • PLC + operator HMI panel

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