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Life Sciences

LIfe Sciences

Test Tube and Cap Identification

Machine vision tools verify test tube and cap presence and dimensions

Test Tube and Cap Identification

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Advantage OEM

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Advantage 100

Advantage 100 Series

Reliable and easy to implement OEM machine vision solution

Clinical diagnostic instruments often must determine the size and shape of various test tubes and test tube caps to maximize throughput and prevent errors. Hand sorting test tubes and caps is time intensive and prone to mistakes.

Develop machine vision workflows

Lab automation relies on repeatable and accurate results. A challenge of measuring test tubes in a clinical instrument is adapting machine vision protocols to customer-specific software, speed requirements and tolerances. Changing requirements midway through development can add months to milestone schedules if machine vision systems lack flexibility and robust validation tools.

Incomplete racks of test tubes can slow workflows by spending time searching for missing test tubes. Equipping clinical instruments with machine vision to recognize a missing test tube can help increase throughput by enabling the equipment to move quickly to the next inspection location.

Robust edge inspection with state-of-the-art shape detection

Clinical instrument software developers rely on Cognex machine vision solutions to provide error-proof results. Cognex Advantage engine products are equipped with robust edge inspection and state-of-the-art shape detection tools that accurately measure test tube geometries to submillimeter tolerances. The same vision tools can be adapted to output the type and shape of test tube caps. Measurements can be made with and without motion, adapting to the needs of various workflows.

The comprehensive set of vision tools, including edge inspection and shape detection tools, are easily accessed through the In-Sight Explorer EasyBuilder interface. In-Sight Explorer creates custom machine vision job files in just minutes and developers are able to revision control and track changes to each job file created.

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