Green Laser CMM Scans Carbon Fiber, Polished Metal
Perceptron‘s ScanR green laser-line 3D metrology scanner is intended for reverse engineering, production-part dimensional inspection and as a complement to 3D printing.
Perceptron‘s ScanR green laser-line 3D metrology scanner is intended for reverse engineering, production-part dimensional inspection and as a complement to 3D printing. Highly reflective materials such as machined aluminum and carbon fiber composites have posed a challenge for laser scanners, requiring part spraying with a powder coat, which inhibits its practical use on repetitive production parts. According to Perceptron, the ScanR laser coordinate measuring machine meets the challenge with wider coverage of color spectrum and reflectivity; improved coverage of materials such as carbon fiber, polished metal and plated metal; increased accuracy with a thinner laser line and higher signal-to-noise ratio; sub-pixel edge detection; and other features.
ScanR integrates with the company’s TouchDMIS metrology software, offering a one-touch scanning interface and enabling initial setup using a tactile probe with subsequent sharing of the generated part coordinate system. Feature extraction from the point cloud enables automatic inspection of part features against nominal feature definitions selected from CAD. Production parts can be programmed to be inspected automatically with scanning zone and parameters adjusted per feature for data acquisition and cycle time optimization.
Related Content
-
Turning Fixed-Body Plug Gages Inside Out
Fixed-body mechanical plug gages provide fast, high-performance measurement for tight-tolerance holes.
-
Rethink Quality Control to Increase Productivity, Decrease Scrap
Verifying parts is essential to documenting quality, and there are a few best practices that can make the quality control process more efficient.
-
Process Control — Leveraging Machine Shop Connectivity in Real Time
Renishaw Central, the company’s new end-to-end process control software, offers a new methodology for producing families of parts through actionable data.