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Background

Optimizing process by using AI for detecting product errors and poor quality at high speed. Overview of the outcome of a process line and sorting low-quality products from high-quality products.

Prerequisites

Camera for detection is already installed. Requires a lightweight, but very fast edge computing solution for running the recognition algorithm and updating the sorting mechanism.

Scope

Real-time image analysis
  • Run image recognition algorithm in less than 100 msec
  • Take action (send action) to sorting mechanism in real time
Collect data and update AI
  • Collect data for historical usage
  • Train AI-algorithm
Integrate 3rd party systems for management and control

Solution

Crosser Node deployed in a Virtual Machine:
  • Connecting to machine camera processing box.
  • Running image recognition locally o Sending anomalies to Machine Execution System (MES)
  • Sending notifications/errors to Machine Engineers and Enterprise System
  • Sending data to AI training in the cloud
  • Crosser Cloud:
  • Customer organization set up with roles
  • Resources library setup

Try Crosser For Free

Start innovating today. How it works:

  1. Get an account
  2. Log in and start designing your flows in the sandbox
  3. Download the Crosser Container to your local test node
  4. Test with real data