IT in Manufacturing


Deep-learning AI made accessible

September 2021 IT in Manufacturing

SICK Automation has launched a set of deep-learning software and services called dStudio, making artificial intelligence (AI) more accessible to the southern African market. This software works with machine vision solutions and simplifies quality inspection of components, assemblies, barcodes, surfaces, food produce and more.

The deep-learning software allows users to set up AI image classification onboard SICK smart devices. This allows these devices to use specially optimised neural networks to make decisions automatically and run accurate and reliable inspections.

dStudio is a SICK web service that can be used to train neural networks that are optimised for various devices, simply by inserting sample images of correct/incorrect examples. The image inference is carried out directly on the device in a short and predictable decision time, without the need for an additional PC. Results are sent to the control system as sensor values. Unlike its predecessors, dStudio removes the laborious process of developing rules and algorithms to identify patterns or defects. This removes the time-consuming process for harder-to-identify patterns/defects, such as leather creases, different nuts, or wood grain.

Intuitive user interface

dStudio offers an intuitive user interface, making it accessible to users without skilled AI knowledge. For more experienced users, the SICK AppSpace software platform allows them to create and customise their own deep learning sensor apps. Training progress and success are shown in clear graphics so that the trained neural network can be assessed prior to running it in an application. Further saving time and implementation costs, all system training takes place in the Cloud, removing the need for additional hardware or software training.

SICK deep learning is supported by the Inspector P 621 2D vision sensor and the SIM 1012 programmable sensor integration machine with SICK’s Picocam or Midicam streaming cameras. In time, the deep learning will also be enabled across both SICK smart 2D and 3D vision sensors, as well as data processing gateways.

“We believe that SICK’s deep learning products are the future of automation,” concludes Grant Joyce, head of sales, marketing and product management at SICK Automation South Africa. “Being accessible and economical, this technology can easily be implemented across Africa, offering massive boosts in efficiency, productivity and safety.”

For more information contact Grant Joyce, SICK Automation Southern Africa, +27 10 060 0558, grant.joyce@sickautomation.co.za, www.sickautomation.co.za


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