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AI & ML Based Laser Inspection ATE

Utilizes advanced laser-based 3D cameras, a comprehensive data acquisition system, and AI-ML-based defect identification for automatic, precise surface defect detection on hot steel plates, eliminating human intervention.

Industry type:
Steel or Metallurgical

Impact

  • User Configurability: Allows users to configure and store numerous product settings directly.
  • Automated Detection: Ensures continuous and automatic detection of surface defects without human intervention.
  • Advanced Imaging: Provides extremely clear and sharp images using cooled thermal imaging technology.

Overview

Our client, a major integrated steel plant, faces challenges with manual surface inspection of steel plates at the New Plate Mill (NPM), RSP. This process is time-consuming, error-prone, and lacks timely feedback for defect containment. To address this, our client plan to introduce a laser-based 3D camera system for automated defect identification, enhancing efficiency and accuracy.

Challenges

  • Current data systems lack efficiency in hazardous environments, hindering inspection processes.
  • Manual inspection in hazardous areas is inefficient, requiring significant time and manpower.
  • Hazardous environments pose challenges for inspectors due to limited visibility and terrain obstacles

Strategy

  • Criteria Settings: Enables setting and saving acceptance and rejection criteria in the database.
  • Calibration Flexibility: Includes a calibration window for adjusting tolerances.
  • Data Management: Offers provision for checking historical data.

Outcome

  • Efficiency and Accuracy: Enhances the efficiency and accuracy of defect identification and quality control.
  • Operator-Friendly Interface: Displays steel plate images with identified defects as they pass through the conveyor.
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