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Phase-measuring deflectometry is a particularly reliable process for measuring reflective or partially reflective surfaces. With its SpecGAGE3D sensor range, ISRA VISION has set new standards and perfected the process.

In a time-saving single measurement step, SpecGAGE3D reliably detects the form and any defects on high-gloss injection-molded components. By comparing the images to the CAD model, the system detects pitch deviations down to the millidiopter range, with local defects being detected right down to the nanometer range. Paint defects, inclusions, injection defects, and other faults are detected, classified, and documented quickly and reliably.

The conclusions drawn from these inspections allow the processes to be adjusted quickly, thereby optimizing productivity – resources and machine running times are saved. Moreover, shorter measurement times enable higher cycle rates to be achieved.

Benefits

  • Fast 100% inspection of specular surfaces for reliable and consistent values
  • 3D shape measurement and defect detection in a single system
  • Clear defect classification and traceability
  • Real-time production monitoring and process control

Form control and defect detection in one measurement

Capture shape errors reliably

Unwanted deformations remain one of the typical defects of injection-molded components. Among other causes, these can occur when the temperature of the mold or in the injected plastic is not set correctly. When it comes to optical components such as head-up displays, distortions in the millidiopter range can significantly impair the component function.

With the help of CAD data, the head-up display mirrors are checked for their correct curvature. The measurement data is compared with the CAD model, and a difference map is created with micrometer accuracy.

At the same time, the surface is checked for local distortions and defects such as waviness, orange peel, inclusions, hillocks.

The tolerable deviation can be checked reliably and efficiently, plus the production process can be controlled by point comparison, profile sections, or area-based evaluation.

Reliable detection of cosmetic defects

Automated, AI-based defect detection detects and classifies surface defects down to a typical defect size of 40 µm.

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