FactoryMind AI

Unexpected machine failures can cause costly downtime, while interpreting sensor data and choosing the right maintenance action can be difficult. FactoryMind AI is an intelligent industrial maintenance decision-support platform designed to make this process smarter, more transparent, and more accessible. Our application allows users to explore simulated industrial machine data and assess potential equipment failure risks using machine learning. When a machine shows signs of a problem, an AI-assisted investigation workflow helps analyze sensor readings, explain possible causes, and suggest appropriate maintenance actions supported by relevant technical knowledge. Unlike a traditional AI chatbot, FactoryMind AI focuses on the complete maintenance decision process. A human technician remains responsible for approving proposed interventions. The platform also aims to evaluate maintenance effectiveness by comparing machine conditions before and after simulated interventions, including a planned comparison against taking no action. Our current development uses OpenRouter as the intended AI inference service, with rule-based diagnostics available as an offline fallback. The prototype uses synthetic data and simulation-based outcomes rather than claiming real-world industrial validation. We are building FactoryMind AI to demonstrate how machine learning, AI reasoning, human oversight, and measurable outcomes can work together in industrial maintenance. Integration with AMD-backed AI infrastructure is planned as the final development phase.