Image recognition AI

Optimizing process by using AI for detecting product errors and poor quality at high speed

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

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