Enhance Your Vision System with Our Specialized Solutions for Cortex
Cortex 3.0 is the machine vision software developed by Bcnvision Group, designed to centralize, manage, and scale industrial vision systems from a single platform.
A single multi-device platform to control all your vision systems, featuring a robust, scalable architecture ready for the industry of the future.
Cortex 3.0 can be extended with optional modules that enhance analysis, traceability, and control capabilities.
Enhancer | Database Statistics Module (CTX-DB)
The CTX-DB module centralizes, analyzes, and visualizes data generated by vision systems for advanced quality control.
Main functionalities:
- Visualization of inspection history
- Analysis of rejection rates
- Statistical control of measurements and features
- Controlled tolerance adjustments
- Statistics by operator, date, shift, or defect type
The module integrates a centralized server, accessible from any device on the network via web browser (Chrome or Edge), and allows data export in CSV format.
It can be installed on a dedicated server or PC, facilitating integration into existing IT infrastructures.
Enhancer | Production Analysis Module (CTX-PRO)
The CTX-PRO module is focused on advanced analysis of the vision system’s performance within the production process.
The Production Analysis Module (CTX-PRO) enables:
- Analyzing quality trends over 60 minutes
- Early detection of process deviations
- Correlation of defects with production parameters
- Improving process efficiency and stability
A key tool for environments where machine vision not only inspects but also adds value to the production process.
Enhancer | VisionBox (CTX-SCADA)
With the VisionBox module, Cortex 3.0 integrates vision system and PLC data into a single application using a unified communication protocol.
Key benefits:
- Machine and vision control from a single software platform
- Real-time monitoring of process and quality variables
- Reduced integration and maintenance costs
An ideal solution to simplify architectures and improve process visibility.
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