Flexxbotics Releases Open-Source Connector Drivers on GitHub

[Cengiz Özemli]

## Flexxbotics Releases Open-Source Connector Drivers on GitHub

Flexxbotics, a company providing workcell digitalization technologies for robot-driven manufacturing, has shared its open-source "Transformers" project on GitHub. These drivers offer industry-standard, production-ready solutions for equipment and automation systems in manufacturing facilities.

The project was developed under the Apache 2.0 license and designed with software-based automation principles to enable open and compatible communication between various tools, machines, and automation systems in manufacturing environments. Transformers connect factory assets such as machines, PLCs, robots, test and control equipment, sensors, and safety systems through a standard abstraction layer using open industrial protocols and customized interfaces.

### Transformers Technical Specifications

• Utilizes asynchronous control systems with parallel data pipelines and multi-threading
• Provides point-to-point integration compatible with over 1000 factory equipment models
• Processes complex data flows, contributing to industrial AI training datasets
• Supports multiple connections between devices, enabling large-scale data sharing

The GitHub repository includes the following production-ready solutions and examples:

• Equipment Transformers that use existing protocols and interfaces such as OPC UA, MQTT, Siemens S7comm, Beckhoff ADS TwinCAT, Fanuc FOCAS2
• Workcell Transformer that coordinates automation logic and manages multi-threaded, asynchronous controls
• Transformer Template for developing new device connector drivers
• Automation scripts that run in real-time via a control configurator and HMI, interacting directly with Transformers

### Practical Applications

• Advanced Process Control (APC), Run-to-Run (R2R) systems, automated production lines, and robotic machine tending
• Process characterization, correlation, and root cause analysis
• Autonomous adjustment of parameters and variables with automated process control
• Coordination of automated processes with multiple operations, digital traceability
• Collection and contextualization of incompatible datasets from different sources for industrial AI training

This innovative integration software enhances data compatibility in manufacturing and automation, supporting operational efficiency and standing out as a significant step in industrial IoT applications.