Freya-Quantum Predictive Maintenance System

Industrial sectors face $864 billion in annual losses due to unexpected equipment failures, with 80% of breakdowns occurring due to undetected anomalies. Traditional AI models struggle with multi-dimensional failure detection, leading to inefficiencies and costly downtime. So, our team developed Freya—a quantum-enhanced predictive maintenance system that combines Quantum State Analysis, AI-driven scheduling, and IBM’s Granite 3.1-8b-instruct AI to predict and prevent failures before they happen. Freya analyzes sensor data in real time, detecting anomalies 48 hours in advance, optimizing maintenance schedules, and reducing downtime by 30%. Key Features: 🔹 Quantum-Enhanced Anomaly Detection – Detects failures invisible to traditional AI 🔹AI-Driven Maintenance Planning – Optimizes scheduling and resource allocation 🔹 IBM Granite AI Core – Industry-trained with 95% prediction accuracy 🔹 SaaS Model for Enterprises – Scalable solution for manufacturing, aerospace, energy, and smart cities By leveraging quantum computing principles and advanced AI, Freya transforms industrial maintenance from a reactive process into a proactive and cost-efficient strategy, ensuring maximum uptime and efficiency.