Edge-toepassing

Step 1: Organize & Categorize 

Gather images of both good and bad quality products and categorize them accordingly. This can involve using existing archived images or installing a camera on the production line to capture real-time images during production.

Step 2: Preprocess Images

Adjust the images through preprocessing techniques to optimize them for analysis by the AI. This may include tasks such as cropping out irrelevant areas to focus only on the pertinent parts needed for analysis.

Step 3: AI Model Creation With just a click of a button

Initiate the creation of the AI model. The AI utilizes a subset of the provided images for training the model and another subset for validating its performance. This streamlined process ensures the swift development and deployment of the AI for product quality analysis, allowing for transparent evaluation of its effectiveness and performance.

Step 4: Configure the Task

Leverage pre-designed templates in low-code platforms to effortlessly configure the hardware and software setup. Define the interactions between the Programmable Logic Controller (PLC), MELSOFT VIXIO, and camera with ease. Direct integration of GigE Vision® cameras allows easy configuration and fine-tuning.

Step 5: Real-time Operation on the Production Line

Initiate the task on the production machine to commence real-time quality analysis. Gain immediate access to a live heatmap visualization of product quality, providing instant insights into production performance. Seamlessly track inspection history for comprehensive traceability functions, ensuring continuous improvement and quality control.