Zeiss' AIMax cloud optical 3D sensor Click image to enlarge

Zeiss Industrial Metrology has launched AIMax cloud optical 3D sensor, a robot-based 3D inline metrology system for sheet metal processing and car body production.

"By capturing dense point clouds, the ZEISS AIMax cloud offers the possibility of measuring multiple features, such as hem edges, rivets, surfaces points and T pins, with just a single capture. The measurement setup is fast and intuitive, and the result is visualized immediately after the measurement in the 3D point cloud. For the user, this is a very comfortable and time-saving solution," says Michael Scheffler, business development manager in the Zeiss Industrial Metrology business group.

Zeiss AIMax cloud can be used both in-line and at-line in robot-based 3D metrology for sheet metal processing and car body construction. Other possible applications include the inspection of assembly and welding processes, gap-and-flush measurements in body shell construction and final assembly in the automotive industry. The strengths of the ZEISS AIMax cloud are particularly beneficial for measurements of features that were previously difficult to analyze such as rivets, nuts behind sheet metal and characteristic design lines.

"The sensor can be used very flexibly and therefore offers genuine benefits to the user," adds Scheffler.

Its short measuring times make the ZEISS AIMax cloud ideal for 100 per cent inspections with short cycle times. The optimized projection technology and the high 3D resolution enable fast, exact measurements, even of tiny features on both sheet metal and paint. The feature extraction in the point cloud offers increased robustness, faster setup times and greater ease of use than traditional image processing. The compact sensor design permits the measurement even of hard-to-reach features, making it ideal for robot-guided usage in in-line metrology.

"Overall, the Zeiss AIMax cloud is a new 3D sensor that will set the standards in robot-based 3D in-line metrology in the future," says Scheffler.

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