Computer Vision in Industry

AIIndustry 4.0Quality

Artificial vision system for automated quality control, optimization of production processes, and operator safety, with reduction of defects and increased efficiency.

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Elements

  • High-resolution industrial cameras
  • Controlled lighting of the inspection area
  • Hardware for image processing (GPU/CPU)
  • Image analysis and Deep Learning software
  • Real-time alarm and notification system

Core technologies

  • Deep Learning algorithms for defect recognition
  • Multi-angle image acquisition system
  • Production flow management software
  • Monitoring and reporting dashboard
  • Integration interface with existing machinery

Results

  • 95% reduction in undetected defects
  • 30% increase in inspection speed
  • 40% decrease in quality control costs
  • Complete traceability of the production process
  • ROI achieved in 12-18 months

    • Vision system architecture

    The system consists of three key interconnected elements. The hardware part includes high-speed cameras and controlled lighting systems that capture images of the product from different angles. The processing module uses trained neural networks to identify industry-specific defects, comparing images with a reference database. The operator interface presents results in real-time and allows configuration of control parameters based on production specifications.

    Implementation management

    Integration into the production line is carried out in progressive phases. It starts with an analysis of the critical points of the process and the definition of control parameters. This is followed by a training phase of the system with samples of conforming and non-conforming products. Personnel are trained on system use and notification management. The implementation includes a period of side-by-side operation with traditional quality control to validate the accuracy of the automatic system.

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