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Deep learning sensor for Industry 4.0

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Sick Automation has developed a sensor solution that operates on the basis of deep learning algorithms. This deep learning technology is used in the industrial environment to specialise the functionality of Sick sensors. In this environment, the sensor learns to process information and therefore receives new functions. In addition, new processes are possible on the basis of adapted sensors. The sensor supplies, processes and analyses data using self-learning algorithms. “We are currently working with deep learning on a pilot project in the lumber industry,” says Grant Joyce, Sick Automation Southern Africa. To ensure optimum use of the raw lumber material, sawmills must know about the conditions in the logs, such as knowing where the age rings and the core are in order to ensure good processing of the lumber. “To find out how the lumber can best be used, we taught the camera to identify these using deep learning,” says Joyce. In the pilot project, SICK was able to increase the material use, improve the quality of the products and avoid wasting resources.

Contact Grance Joyce, SICK Automation, Tel 010 060-0550, grant.joyce@sickautomation.co.za

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