MEASUREMENT & MONITORING INTELLIGENT INSPECTION
SICK
SICK Launches Compact 2D Vision Camera with Deep Learning App Onboard
SICK is launching its first vision camera with a pre-installed Deep Learning app onboard to make it simple to create custom quality inspections of complex or irregular-shaped produce , products or packaging . The system will bring opportunities for food industry operators to automate vision inspections , for example of naturally-grown produce , that may have previously defied automation using traditional systems .
PRACTICAL AND AFFORDABLE AI CLASSIFICATION
The SICK Intelligent Inspection Deep Learning App runs on SICK ’ s newly launched Inspector P621 2D programmable vision camera . The all-inone package enables machine builders and food processors to set up Artificial Intelligence vision classifications in a fraction of the time and cost it would take to set up complex inspections using traditional vision inspections based on pre-set rules .
Where it has previously been very challenging to achieve consistently robust and repeatable quality inspections , with SICK Intelligent Inspection they can now be mastered with high levels of reliability and availability . Automation is therefore practical and affordable for complex imaging tasks such as sorting fresh fruit and vegetables or inspecting packaging that may get easily deformed , for example .
Neil Sandhu , SICK ’ s UK Product Manager for Imaging , Measurement and Ranging explains : “ By embedding the Intelligent Inspection App onto SICK ’ s Inspector P621 deep learning camera , SICK has made it possible for users to purchase a ready-made package that uses artificial intelligence to run complex vision inspections with ease .
“ Users are guided through an intuitive process that teaches the system how to recognise ‘ good and bad ’ examples using SICK ’ s specially-optimised neural networks in the cloud .”
Because it runs directly on the camera , the SICK Intelligent Inspection app does not require any additional hardware .
INTUITIVE STEP-BY-STEP PROCESS
Using the SICK Inspector 621 ’ s in-built image capture tool , users begin by collecting example images of their product in realistic production conditions . Guided step-by-step through the intuitive graphic interface , the system prompts them to sort the images into classes . Using SICK ’ s dStudio service , the pre-sorted images are uploaded to the Cloud where the image training process is completed by the neural network . The user can then apply further production images to evaluate and adjust the system .
Once the user is satisfied , the neural network is downloaded to the Inspector P621 camera where it can begin to take decisions automatically with no further Cloud connection necessary . Results are output to the control system as sensor values and digital I / O .
The image inference is carried out directly on the device , so there is no need for an additional PC . As the system training is done in the Cloud , there is also no need for separate training hardware or software , saving on implementation time and cost .
“ Because it runs directly on the camera , the SICK Intelligent Inspection app does not require any additional hardware ,” Sandhu continues . “ So , users can automate complex vision inspections for a much lower cost of ownership . They can now consider automating quality inspections of products or goods that have just proved too difficult previously .
“ Even better , the system can be set up in no time at all . Users may be able to manage the process themselves . However , if needed , SICK is also offering services to support customers through the feasibility , commissioning and neural network training process .”
Users also have access to a large set of traditional machine vision tools installed
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