How Can I Integrate 3D Scanning Data From A Structured Blue Light Scanner With Our Existing GD&T (Geometric Dimensioning And Tolerancing) Framework In Our CAD Software To Automate The Detection Of Non-conformities In Cast Aluminum Parts, Specifically For The Identification Of Porosity And Misalignment Of Critical Features, And What Are The Implications For Our AS9100D Quality Management System?

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Integrating 3D scanning data with GD&T in CAD for cast aluminum parts involves a structured approach to automate defect detection and comply with AS9100D standards. Here's a comprehensive plan:

Integration Process

  1. Data Import and Alignment:

    • Export GD&T Specs: Transfer GD&T specifications from CAD software into a compatible format for 3D scanning tools like PolyWorks or Geomagic.
    • 3D Scan Data: Use a structured blue light scanner to capture part data, outputting as STL or point cloud files.
    • Registration: Align scan data with the CAD model using registration techniques to ensure a common coordinate system.

  2. Automated Inspection:

    • Software Integration: Use scanning software to compare scan data against GD&T specs. Set up inspection templates for porosity and misalignment detection.
    • Threshold Settings: Define acceptable thresholds for surface deviations and feature positions to flag non-conformities.

  3. Technical Considerations:

    • Environmental Control: Optimize scanning environment for accuracy, considering lighting and surface finish.
    • Hardware Requirements: Ensure sufficient computational power to handle large datasets.

AS9100D Compliance

  1. Documentation Control:

    • Maintain controlled documents for GD&T frameworks and inspection templates, ensuring version control and access management.

  2. Training and Competence:

    • Provide updated training for the quality team on the new system, including data interpretation and system maintenance.

  3. Risk Management:

    • Assess risks like false results and implement mitigations such as calibration checks and cross-verification.

  4. Traceability and Record-Keeping:

    • Store inspection data for traceability, useful for audits and quality records.

  5. Corrective Actions:

    • Establish processes for handling non-conformities, including containment and root cause analysis.

  6. Internal Audits:

    • Include the new system in audit plans, ensuring adherence to AS9100D requirements.

  7. Supplier Control:

    • Ensure external software or services meet quality standards and compatibility.

  8. Continuous Improvement:

    • Use inspection data to refine processes and improve product quality.

Challenges and Solutions

  • Accuracy and Verification: Address potential false positives/negatives with manual verification for critical defects.
  • Software Automation: Develop scripts or macros for automating comparisons, possibly using APIs.

Summary

This integration enhances quality control by automating defect detection, reducing human error, and providing detailed data for compliance and improvement. By addressing technical and procedural aspects, the system ensures AS9100D compliance and supports ongoing quality management.