SimuFactory

Project Description: SimuFactory The Problem In the world of industrial automation, training technicians on live PLC (Programmable Logic Controller) systems is high-risk and high-cost. A single wrong command in a real factory can lead to catastrophic hardware failure, expensive production downtime, or severe safety hazards. However, traditional simulators are often static and fail to teach the "critical thinking" required for real-world troubleshooting. SimuFactory is a high-fidelity, AI-powered training ecosystem that implements a Cognitive Digital Twin of an industrial cell. Instead of a simple "correct/incorrect" feedback loop, SimuFactory utilizes a Socratic Coaching Engine. Powered by Llama-3, the AI acts as a senior engineer, guiding the trainee through complex faults using targeted questions and contextual hints, forcing the user to diagnose the root cause rather than simply following a manual. To ensure industrial-grade safety, we implemented a sophisticated Dual-LLM Architecture. While Llama-3 handles the pedagogical coaching, we integrated Gemma-2 as a dedicated Real-time Safety Auditor. This "Watchdog" model intercepts every terminal command, analyzing it against the current factory state to detect ISO 26262 safety violations. If a command is deemed dangerous, the auditor blocks the action and triggers a "Thermal Trip" or "E-Stop" simulation, teaching the trainee the real-world consequences of unsafe practices. SimuFactory is designed for Edge Deployment on AMD hardware. By leveraging the AMD ROCm™ stack and the massive memory bandwidth of the Instinct™ MI300X, we achieve ultra-low latency inference that allows the simulation and AI to react in real-time. Most importantly, our architecture ensures Data Sovereignty. In a real-world deployment, sensitive factory telemetry and PLC logic never leave the local network, removing the security risks associated with cloud-based AI and making SimuFactory a viable solution for high-security industrial environments